problem stringlengths 1.19k 65.4k | solution stringlengths 1.19k 67.5k | topic stringlengths 5 80 |
|---|---|---|
---
title
intersecting_segments
---
# Search for a pair of intersecting segments
Given $n$ line segments on the plane. It is required to check whether at least two of them intersect with each other.
If the answer is yes, then print this pair of intersecting segments; it is enough to choose any of them among several ... | ---
title
intersecting_segments
---
# Search for a pair of intersecting segments
Given $n$ line segments on the plane. It is required to check whether at least two of them intersect with each other.
If the answer is yes, then print this pair of intersecting segments; it is enough to choose any of them among several ... | Search for a pair of intersecting segments |
---
title
segments_intersection_checking
---
# Check if two segments intersect
You are given two segments $(a, b)$ and $(c, d)$.
You have to check if they intersect.
Of course, you may find their intersection and check if it isn't empty, but this can't be done in integers for segments with integer coordinates.
The a... | ---
title
segments_intersection_checking
---
# Check if two segments intersect
You are given two segments $(a, b)$ and $(c, d)$.
You have to check if they intersect.
Of course, you may find their intersection and check if it isn't empty, but this can't be done in integers for segments with integer coordinates.
The a... | Check if two segments intersect |
---
title
- Original
---
# Convex hull trick and Li Chao tree
Consider the following problem. There are $n$ cities. You want to travel from city $1$ to city $n$ by car. To do this you have to buy some gasoline. It is known that a liter of gasoline costs $cost_k$ in the $k^{th}$ city. Initially your fuel tank is emp... | ---
title
- Original
---
# Convex hull trick and Li Chao tree
Consider the following problem. There are $n$ cities. You want to travel from city $1$ to city $n$ by car. To do this you have to buy some gasoline. It is known that a liter of gasoline costs $cost_k$ in the $k^{th}$ city. Initially your fuel tank is emp... | Convex hull trick and Li Chao tree |
---
title
- Original
---
# Basic Geometry
In this article we will consider basic operations on points in Euclidean space which maintains the foundation of the whole analytical geometry.
We will consider for each point $\mathbf r$ the vector $\vec{\mathbf r}$ directed from $\mathbf 0$ to $\mathbf r$.
Later we will n... | ---
title
- Original
---
# Basic Geometry
In this article we will consider basic operations on points in Euclidean space which maintains the foundation of the whole analytical geometry.
We will consider for each point $\mathbf r$ the vector $\vec{\mathbf r}$ directed from $\mathbf 0$ to $\mathbf r$.
Later we will n... | Basic Geometry |
---
title
circles_intersection
---
# Circle-Circle Intersection
You are given two circles on a 2D plane, each one described as coordinates of its center and its radius. Find the points of their intersection (possible cases: one or two points, no intersection or circles coincide).
## Solution
Let's reduce this prob... | ---
title
circles_intersection
---
# Circle-Circle Intersection
You are given two circles on a 2D plane, each one described as coordinates of its center and its radius. Find the points of their intersection (possible cases: one or two points, no intersection or circles coincide).
## Solution
Let's reduce this prob... | Circle-Circle Intersection |
---
title
segments_intersection
---
# Finding intersection of two segments
You are given two segments AB and CD, described as pairs of their endpoints. Each segment can be a single point if its endpoints are the same.
You have to find the intersection of these segments, which can be empty (if the segments don't int... | ---
title
segments_intersection
---
# Finding intersection of two segments
You are given two segments AB and CD, described as pairs of their endpoints. Each segment can be a single point if its endpoints are the same.
You have to find the intersection of these segments, which can be empty (if the segments don't int... | Finding intersection of two segments |
---
title
convex_hull_graham
---
# Convex Hull construction
In this article we will discuss the problem of constructing a convex hull from a set of points.
Consider $N$ points given on a plane, and the objective is to generate a convex hull, i.e. the smallest
convex polygon that contains all the given points.
We w... | ---
title
convex_hull_graham
---
# Convex Hull construction
In this article we will discuss the problem of constructing a convex hull from a set of points.
Consider $N$ points given on a plane, and the objective is to generate a convex hull, i.e. the smallest
convex polygon that contains all the given points.
We w... | Convex Hull construction |
---
title
voronoi_diagram_2d_n4
---
# Delaunay triangulation and Voronoi diagram
Consider a set $\{p_i\}$ of points on the plane.
A **Voronoi diagram** $V(\{p_i\})$ of $\{p_i\}$ is a partition of the plane into $n$ regions $V_i$, where $V_i = \{p\in\mathbb{R}^2;\ \rho(p, p_i) = \min\ \rho(p, p_k)\}$.
The cells of th... | ---
title
voronoi_diagram_2d_n4
---
# Delaunay triangulation and Voronoi diagram
Consider a set $\{p_i\}$ of points on the plane.
A **Voronoi diagram** $V(\{p_i\})$ of $\{p_i\}$ is a partition of the plane into $n$ regions $V_i$, where $V_i = \{p\in\mathbb{R}^2;\ \rho(p, p_i) = \min\ \rho(p, p_k)\}$.
The cells of th... | Delaunay triangulation and Voronoi diagram |
---
title
nearest_points
---
# Finding the nearest pair of points
## Problem statement
Given $n$ points on the plane. Each point $p_i$ is defined by its coordinates $(x_i,y_i)$. It is required to find among them two such points, such that the distance between them is minimal:
$$ \min_{\scriptstyle i, j=0 \ldots n-... | ---
title
nearest_points
---
# Finding the nearest pair of points
## Problem statement
Given $n$ points on the plane. Each point $p_i$ is defined by its coordinates $(x_i,y_i)$. It is required to find among them two such points, such that the distance between them is minimal:
$$ \min_{\scriptstyle i, j=0 \ldots n-... | Finding the nearest pair of points |
---
title: Point location in O(log n)
title
- Original
---
# Point location in $O(log n)$
Consider the following problem: you are given a [planar subdivision](https://en.wikipedia.org/wiki/Planar_straight-line_graph) without no vertices of degree one and zero, and a lot of queries.
Each query is a point, for which w... | ---
title: Point location in O(log n)
title
- Original
---
# Point location in $O(log n)$
Consider the following problem: you are given a [planar subdivision](https://en.wikipedia.org/wiki/Planar_straight-line_graph) without no vertices of degree one and zero, and a lot of queries.
Each query is a point, for which w... | Point location in $O(log n)$ |
---
title: Finding faces of a planar graph
title
facets
---
# Finding faces of a planar graph
Consider a graph $G$ with $n$ vertices and $m$ edges, which can be drawn on a plane in such a way that two edges intersect only at a common vertex (if it exists).
Such graphs are called **planar**. Now suppose that we are gi... | ---
title: Finding faces of a planar graph
title
facets
---
# Finding faces of a planar graph
Consider a graph $G$ with $n$ vertices and $m$ edges, which can be drawn on a plane in such a way that two edges intersect only at a common vertex (if it exists).
Such graphs are called **planar**. Now suppose that we are gi... | Finding faces of a planar graph |
---
title
pick_grid_theorem
---
# Pick's Theorem
A polygon without self-intersections is called lattice if all its vertices have integer coordinates in some 2D grid. Pick's theorem provides a way to compute the area of this polygon through the number of vertices that are lying on the boundary and the number of verti... | ---
title
pick_grid_theorem
---
# Pick's Theorem
A polygon without self-intersections is called lattice if all its vertices have integer coordinates in some 2D grid. Pick's theorem provides a way to compute the area of this polygon through the number of vertices that are lying on the boundary and the number of verti... | Pick's Theorem |
---
title
oriented_area
---
# Oriented area of a triangle
Given three points $p_1$, $p_2$ and $p_3$, calculate an oriented (signed) area of a triangle formed by them. The sign of the area is determined in the following way: imagine you are standing in the plane at point $p_1$ and are facing $p_2$. You go to $p_2$ an... | ---
title
oriented_area
---
# Oriented area of a triangle
Given three points $p_1$, $p_2$ and $p_3$, calculate an oriented (signed) area of a triangle formed by them. The sign of the area is determined in the following way: imagine you are standing in the plane at point $p_1$ and are facing $p_2$. You go to $p_2$ an... | Oriented area of a triangle |
---
title: Check if point belongs to the convex polygon in O(log N)
title
pt_in_polygon
---
# Check if point belongs to the convex polygon in $O(\log N)$
Consider the following problem: you are given a convex polygon with integer vertices and a lot of queries.
Each query is a point, for which we should determine whet... | ---
title: Check if point belongs to the convex polygon in O(log N)
title
pt_in_polygon
---
# Check if point belongs to the convex polygon in $O(\log N)$
Consider the following problem: you are given a convex polygon with integer vertices and a lot of queries.
Each query is a point, for which we should determine whet... | Check if point belongs to the convex polygon in $O(\log N)$ |
---
title
lines_intersection
---
# Intersection Point of Lines
You are given two lines, described via the equations $a_1 x + b_1 y + c_1 = 0$ and $a_2 x + b_2 y + c_2 = 0$.
We have to find the intersection point of the lines, or determine that the lines are parallel.
## Solution
If two lines are not parallel, the... | ---
title
lines_intersection
---
# Intersection Point of Lines
You are given two lines, described via the equations $a_1 x + b_1 y + c_1 = 0$ and $a_2 x + b_2 y + c_2 = 0$.
We have to find the intersection point of the lines, or determine that the lines are parallel.
## Solution
If two lines are not parallel, the... | Intersection Point of Lines |
---
title
- Original
---
# Half-plane intersection
In this article we will discuss the problem of computing the intersection of a set of half-planes. Such an intersection can be conveniently represented as a convex region/polygon, where every point inside of it is also inside all of the half-planes, and it is this ... | ---
title
- Original
---
# Half-plane intersection
In this article we will discuss the problem of computing the intersection of a set of half-planes. Such an intersection can be conveniently represented as a convex region/polygon, where every point inside of it is also inside all of the half-planes, and it is this ... | Half-plane intersection |
---
title
circle_tangents
---
# Finding common tangents to two circles
Given two circles. It is required to find all their common tangents, i.e. all such lines that touch both circles simultaneously.
The described algorithm will also work in the case when one (or both) circles degenerate into points. Thus, this alg... | ---
title
circle_tangents
---
# Finding common tangents to two circles
Given two circles. It is required to find all their common tangents, i.e. all such lines that touch both circles simultaneously.
The described algorithm will also work in the case when one (or both) circles degenerate into points. Thus, this alg... | Finding common tangents to two circles |
---
title: Finding area of simple polygon in O(N)
title
polygon_area
---
# Finding area of simple polygon in $O(N)$
Let a simple polygon (i.e. without self intersection, not necessarily convex) be given. It is required to calculate its area given its vertices.
## Method 1
This is easy to do if we go through all edg... | ---
title: Finding area of simple polygon in O(N)
title
polygon_area
---
# Finding area of simple polygon in $O(N)$
Let a simple polygon (i.e. without self intersection, not necessarily convex) be given. It is required to calculate its area given its vertices.
## Method 1
This is easy to do if we go through all edg... | Finding area of simple polygon in $O(N)$ |
---
title
circle_line_intersection
---
# Circle-Line Intersection
Given the coordinates of the center of a circle and its radius, and the equation of a line, you're required to find the points of intersection.
## Solution
Instead of solving the system of two equations, we will approach the problem geometrically. T... | ---
title
circle_line_intersection
---
# Circle-Line Intersection
Given the coordinates of the center of a circle and its radius, and the equation of a line, you're required to find the points of intersection.
## Solution
Instead of solving the system of two equations, we will approach the problem geometrically. T... | Circle-Line Intersection |
---
title
- Original
---
# Lattice points inside non-lattice polygon
For lattice polygons there is Pick's formula to enumerate the lattice points inside the polygon.
What about polygons with arbitrary vertices?
Let's process each of the polygon's edges individually, and after that we may sum up the amounts of latt... | ---
title
- Original
---
# Lattice points inside non-lattice polygon
For lattice polygons there is Pick's formula to enumerate the lattice points inside the polygon.
What about polygons with arbitrary vertices?
Let's process each of the polygon's edges individually, and after that we may sum up the amounts of latt... | Lattice points inside non-lattice polygon |
---
title
- Original
---
# Minkowski sum of convex polygons
## Definition
Consider two sets $A$ and $B$ of points on a plane. Minkowski sum $A + B$ is defined as $\{a + b| a \in A, b \in B\}$.
Here we will consider the case when $A$ and $B$ consist of convex polygons $P$ and $Q$ with their interiors.
Throughout thi... | ---
title
- Original
---
# Minkowski sum of convex polygons
## Definition
Consider two sets $A$ and $B$ of points on a plane. Minkowski sum $A + B$ is defined as $\{a + b| a \in A, b \in B\}$.
Here we will consider the case when $A$ and $B$ consist of convex polygons $P$ and $Q$ with their interiors.
Throughout thi... | Minkowski sum of convex polygons |
---
title
length_of_segments_union
---
# Length of the union of segments
Given $n$ segments on a line, each described by a pair of coordinates $(a_{i1}, a_{i2})$.
We have to find the length of their union.
The following algorithm was proposed by Klee in 1977.
It works in $O(n\log n)$ and has been proven to be the a... | ---
title
length_of_segments_union
---
# Length of the union of segments
Given $n$ segments on a line, each described by a pair of coordinates $(a_{i1}, a_{i2})$.
We have to find the length of their union.
The following algorithm was proposed by Klee in 1977.
It works in $O(n\log n)$ and has been proven to be the a... | Length of the union of segments |
---
title
segment_to_line
---
# Finding the equation of a line for a segment
The task is: given the coordinates of the ends of a segment, construct a line passing through it.
We assume that the segment is non-degenerate, i.e. has a length greater than zero (otherwise, of course, infinitely many different lines pass... | ---
title
segment_to_line
---
# Finding the equation of a line for a segment
The task is: given the coordinates of the ends of a segment, construct a line passing through it.
We assume that the segment is non-degenerate, i.e. has a length greater than zero (otherwise, of course, infinitely many different lines pass... | Finding the equation of a line for a segment |
---
title
triangles_union
---
# Vertical decomposition
## Overview
Vertical decomposition is a powerful technique used in various geometry problems. The general idea is to cut the plane into several vertical stripes
with some "good" properties and solve the problem for these stripes independently. We will illustrate... | ---
title
triangles_union
---
# Vertical decomposition
## Overview
Vertical decomposition is a powerful technique used in various geometry problems. The general idea is to cut the plane into several vertical stripes
with some "good" properties and solve the problem for these stripes independently. We will illustrate... | Vertical decomposition |
---
title
- Original
---
# Knuth's Optimization
Knuth's optimization, also known as the Knuth-Yao Speedup, is a special case of dynamic programming on ranges, that can optimize the time complexity of solutions by a linear factor, from $O(n^3)$ for standard range DP to $O(n^2)$.
## Conditions
The Speedup is applie... | ---
title
- Original
---
# Knuth's Optimization
Knuth's optimization, also known as the Knuth-Yao Speedup, is a special case of dynamic programming on ranges, that can optimize the time complexity of solutions by a linear factor, from $O(n^3)$ for standard range DP to $O(n^2)$.
## Conditions
The Speedup is applie... | Knuth's Optimization |
---
title
maximum_zero_submatrix
---
# Finding the largest zero submatrix
You are given a matrix with `n` rows and `m` columns. Find the largest submatrix consisting of only zeros (a submatrix is a rectangular area of the matrix).
## Algorithm
Elements of the matrix will be `a[i][j]`, where `i = 0...n - 1`, `j = 0... | ---
title
maximum_zero_submatrix
---
# Finding the largest zero submatrix
You are given a matrix with `n` rows and `m` columns. Find the largest submatrix consisting of only zeros (a submatrix is a rectangular area of the matrix).
## Algorithm
Elements of the matrix will be `a[i][j]`, where `i = 0...n - 1`, `j = 0... | Finding the largest zero submatrix |
---
title
profile_dynamics
---
# Dynamic Programming on Broken Profile. Problem "Parquet"
Common problems solved using DP on broken profile include:
- finding number of ways to fully fill an area (e.g. chessboard/grid) with some figures (e.g. dominoes)
- finding a way to fill an area with minimum number of figures
... | ---
title
profile_dynamics
---
# Dynamic Programming on Broken Profile. Problem "Parquet"
Common problems solved using DP on broken profile include:
- finding number of ways to fully fill an area (e.g. chessboard/grid) with some figures (e.g. dominoes)
- finding a way to fill an area with minimum number of figures
... | Dynamic Programming on Broken Profile. Problem "Parquet" |
---
title
- Original
---
# Divide and Conquer DP
Divide and Conquer is a dynamic programming optimization.
### Preconditions
Some dynamic programming problems have a recurrence of this form:
$$
dp(i, j) = \min_{0 \leq k \leq j} \\{ dp(i - 1, k - 1) + C(k, j) \\}
$$
where $C(k, j)$ is a cost function and $dp(i, ... | ---
title
- Original
---
# Divide and Conquer DP
Divide and Conquer is a dynamic programming optimization.
### Preconditions
Some dynamic programming problems have a recurrence of this form:
$$
dp(i, j) = \min_{0 \leq k \leq j} \\{ dp(i - 1, k - 1) + C(k, j) \\}
$$
where $C(k, j)$ is a cost function and $dp(i, ... | Divide and Conquer DP |
---
title
maximum_average_segment
---
# Search the subarray with the maximum/minimum sum
Here, we consider the problem of finding a subarray with maximum sum, as well as some of its variations (including the algorithm for solving this problem online).
## Problem statement
Given an array of numbers $a[1 \ldots n]$.... | ---
title
maximum_average_segment
---
# Search the subarray with the maximum/minimum sum
Here, we consider the problem of finding a subarray with maximum sum, as well as some of its variations (including the algorithm for solving this problem online).
## Problem statement
Given an array of numbers $a[1 \ldots n]$.... | Search the subarray with the maximum/minimum sum |
---
title
joseph_problem
---
# Josephus Problem
## Statement
We are given the natural numbers $n$ and $k$.
All natural numbers from $1$ to $n$ are written in a circle.
First, count the $k$-th number starting from the first one and delete it.
Then $k$ numbers are counted starting from the next one and the $k$-th on... | ---
title
joseph_problem
---
# Josephus Problem
## Statement
We are given the natural numbers $n$ and $k$.
All natural numbers from $1$ to $n$ are written in a circle.
First, count the $k$-th number starting from the first one and delete it.
Then $k$ numbers are counted starting from the next one and the $k$-th on... | Josephus Problem |
---
title
stern_brocot_farey
---
# The Stern-Brocot tree and Farey sequences
## Stern-Brocot tree
The Stern-Brocot tree is an elegant construction to represent the set of all positive fractions. It was independently discovered by German mathematician Moritz Stern in 1858 and by French watchmaker Achille Brocot in 1... | ---
title
stern_brocot_farey
---
# The Stern-Brocot tree and Farey sequences
## Stern-Brocot tree
The Stern-Brocot tree is an elegant construction to represent the set of all positive fractions. It was independently discovered by German mathematician Moritz Stern in 1858 and by French watchmaker Achille Brocot in 1... | The Stern-Brocot tree and Farey sequences |
---
title
15_puzzle
---
# 15 Puzzle Game: Existence Of The Solution
This game is played on a $4 \times 4$ board. On this board there are $15$ playing tiles numbered from 1 to 15. One cell is left empty (denoted by 0). You need to get the board to the position presented below by repeatedly moving one of the tiles to ... | ---
title
15_puzzle
---
# 15 Puzzle Game: Existence Of The Solution
This game is played on a $4 \times 4$ board. On this board there are $15$ playing tiles numbered from 1 to 15. One cell is left empty (denoted by 0). You need to get the board to the position presented below by repeatedly moving one of the tiles to ... | 15 Puzzle Game: Existence Of The Solution |
---
title
dijkstra
---
# Dijkstra Algorithm
You are given a directed or undirected weighted graph with $n$ vertices and $m$ edges. The weights of all edges are non-negative. You are also given a starting vertex $s$. This article discusses finding the lengths of the shortest paths from a starting vertex $s$ to all ot... | ---
title
dijkstra
---
# Dijkstra Algorithm
You are given a directed or undirected weighted graph with $n$ vertices and $m$ edges. The weights of all edges are non-negative. You are also given a starting vertex $s$. This article discusses finding the lengths of the shortest paths from a starting vertex $s$ to all ot... | Dijkstra Algorithm |
---
title
tree_painting
---
# Paint the edges of the tree
This is a fairly common task. Given a tree $G$ with $N$ vertices. There are two types of queries: the first one is to paint an edge, the second one is to query the number of colored edges between two vertices.
Here we will describe a fairly simple solution (... | ---
title
tree_painting
---
# Paint the edges of the tree
This is a fairly common task. Given a tree $G$ with $N$ vertices. There are two types of queries: the first one is to paint an edge, the second one is to query the number of colored edges between two vertices.
Here we will describe a fairly simple solution (... | Paint the edges of the tree |
---
title
flow_with_limits
---
# Flows with demands
In a normal flow network the flow of an edge is only limited by the capacity $c(e)$ from above and by 0 from below.
In this article we will discuss flow networks, where we additionally require the flow of each edge to have a certain amount, i.e. we bound the flow f... | ---
title
flow_with_limits
---
# Flows with demands
In a normal flow network the flow of an edge is only limited by the capacity $c(e)$ from above and by 0 from below.
In this article we will discuss flow networks, where we additionally require the flow of each edge to have a certain amount, i.e. we bound the flow f... | Flows with demands |
---
title
fixed_length_paths
---
# Number of paths of fixed length / Shortest paths of fixed length
The following article describes solutions to these two problems built on the same idea:
reduce the problem to the construction of matrix and compute the solution with the usual matrix multiplication or with a modified... | ---
title
fixed_length_paths
---
# Number of paths of fixed length / Shortest paths of fixed length
The following article describes solutions to these two problems built on the same idea:
reduce the problem to the construction of matrix and compute the solution with the usual matrix multiplication or with a modified... | Number of paths of fixed length / Shortest paths of fixed length |
---
title
kuhn_matching
---
# Kuhn's Algorithm for Maximum Bipartite Matching
## Problem
You are given a bipartite graph $G$ containing $n$ vertices and $m$ edges. Find the maximum matching, i.e., select as many edges as possible so
that no selected edge shares a vertex with any other selected edge.
## Algorithm D... | ---
title
kuhn_matching
---
# Kuhn's Algorithm for Maximum Bipartite Matching
## Problem
You are given a bipartite graph $G$ containing $n$ vertices and $m$ edges. Find the maximum matching, i.e., select as many edges as possible so
that no selected edge shares a vertex with any other selected edge.
## Algorithm D... | Kuhn's Algorithm for Maximum Bipartite Matching |
---
title
strong_connected_components
---
# Finding strongly connected components / Building condensation graph
## Definitions
You are given a directed graph $G$ with vertices $V$ and edges $E$. It is possible that there are loops and multiple edges. Let's denote $n$ as number of vertices and $m$ as number of edges ... | ---
title
strong_connected_components
---
# Finding strongly connected components / Building condensation graph
## Definitions
You are given a directed graph $G$ with vertices $V$ and edges $E$. It is possible that there are loops and multiple edges. Let's denote $n$ as number of vertices and $m$ as number of edges ... | Finding strongly connected components / Building condensation graph |
---
title
- Original
---
# Maximum flow - MPM algorithm
MPM (Malhotra, Pramodh-Kumar and Maheshwari) algorithm solves the maximum flow problem in $O(V^3)$. This algorithm is similar to [Dinic's algorithm](dinic.md).
## Algorithm
Like Dinic's algorithm, MPM runs in phases, during each phase we find the blocking fl... | ---
title
- Original
---
# Maximum flow - MPM algorithm
MPM (Malhotra, Pramodh-Kumar and Maheshwari) algorithm solves the maximum flow problem in $O(V^3)$. This algorithm is similar to [Dinic's algorithm](dinic.md).
## Algorithm
Like Dinic's algorithm, MPM runs in phases, during each phase we find the blocking fl... | Maximum flow - MPM algorithm |
---
title
topological_sort
---
# Topological Sorting
You are given a directed graph with $n$ vertices and $m$ edges.
You have to find an **order of the vertices**, so that every edge leads from the vertex with a smaller index to a vertex with a larger one.
In other words, you want to find a permutation of the verti... | ---
title
topological_sort
---
# Topological Sorting
You are given a directed graph with $n$ vertices and $m$ edges.
You have to find an **order of the vertices**, so that every edge leads from the vertex with a smaller index to a vertex with a larger one.
In other words, you want to find a permutation of the verti... | Topological Sorting |
---
title
prufer_code_cayley_formula
---
# Prüfer code
In this article we will look at the so-called **Prüfer code** (or Prüfer sequence), which is a way of encoding a labeled tree into a sequence of numbers in a unique way.
With the help of the Prüfer code we will prove **Cayley's formula** (which specified the nu... | ---
title
prufer_code_cayley_formula
---
# Prüfer code
In this article we will look at the so-called **Prüfer code** (or Prüfer sequence), which is a way of encoding a labeled tree into a sequence of numbers in a unique way.
With the help of the Prüfer code we will prove **Cayley's formula** (which specified the nu... | Prüfer code |
---
title
- rib_connectivity
- vertex_connectivity
---
# Edge connectivity / Vertex connectivity
## Definition
Given an undirected graph $G$ with $n$ vertices and $m$ edges.
Both the edge connectivity and the vertex connectivity are characteristics describing the graph.
### Edge connectivity
The **edge connec... | ---
title
- rib_connectivity
- vertex_connectivity
---
# Edge connectivity / Vertex connectivity
## Definition
Given an undirected graph $G$ with $n$ vertices and $m$ edges.
Both the edge connectivity and the vertex connectivity are characteristics describing the graph.
### Edge connectivity
The **edge connec... | Edge connectivity / Vertex connectivity |
---
title
dinic
---
# Maximum flow - Dinic's algorithm
Dinic's algorithm solves the maximum flow problem in $O(V^2E)$. The maximum flow problem is defined in this article [Maximum flow - Ford-Fulkerson and Edmonds-Karp](edmonds_karp.md). This algorithm was discovered by Yefim Dinitz in 1970.
## Definitions
A **res... | ---
title
dinic
---
# Maximum flow - Dinic's algorithm
Dinic's algorithm solves the maximum flow problem in $O(V^2E)$. The maximum flow problem is defined in this article [Maximum flow - Ford-Fulkerson and Edmonds-Karp](edmonds_karp.md). This algorithm was discovered by Yefim Dinitz in 1970.
## Definitions
A **res... | Maximum flow - Dinic's algorithm |
---
title: Finding the Eulerian path in O(M)
title
euler_path
---
# Finding the Eulerian path in $O(M)$
A Eulerian path is a path in a graph that passes through all of its edges exactly once.
A Eulerian cycle is a Eulerian path that is a cycle.
The problem is to find the Eulerian path in an **undirected multigraph w... | ---
title: Finding the Eulerian path in O(M)
title
euler_path
---
# Finding the Eulerian path in $O(M)$
A Eulerian path is a path in a graph that passes through all of its edges exactly once.
A Eulerian cycle is a Eulerian path that is a cycle.
The problem is to find the Eulerian path in an **undirected multigraph w... | Finding the Eulerian path in $O(M)$ |
---
title
bridge_searching_online
---
# Finding Bridges Online
We are given an undirected graph.
A bridge is an edge whose removal makes the graph disconnected (or, more precisely, increases the number of connected components).
Our task is to find all the bridges in the given graph.
Informally this task can be put ... | ---
title
bridge_searching_online
---
# Finding Bridges Online
We are given an undirected graph.
A bridge is an edge whose removal makes the graph disconnected (or, more precisely, increases the number of connected components).
Our task is to find all the bridges in the given graph.
Informally this task can be put ... | Finding Bridges Online |
---
title
negative_cycle
---
# Finding a negative cycle in the graph
You are given a directed weighted graph $G$ with $N$ vertices and $M$ edges. Find any cycle of negative weight in it, if such a cycle exists.
In another formulation of the problem you have to find all pairs of vertices which have a path of arbitra... | ---
title
negative_cycle
---
# Finding a negative cycle in the graph
You are given a directed weighted graph $G$ with $N$ vertices and $M$ edges. Find any cycle of negative weight in it, if such a cycle exists.
In another formulation of the problem you have to find all pairs of vertices which have a path of arbitra... | Finding a negative cycle in the graph |
---
title
dfs
---
# Depth First Search
Depth First Search is one of the main graph algorithms.
Depth First Search finds the lexicographical first path in the graph from a source vertex $u$ to each vertex.
Depth First Search will also find the shortest paths in a tree (because there only exists one simple path), but... | ---
title
dfs
---
# Depth First Search
Depth First Search is one of the main graph algorithms.
Depth First Search finds the lexicographical first path in the graph from a source vertex $u$ to each vertex.
Depth First Search will also find the shortest paths in a tree (because there only exists one simple path), but... | Depth First Search |
---
title
mst_prim
---
# Minimum spanning tree - Prim's algorithm
Given a weighted, undirected graph $G$ with $n$ vertices and $m$ edges.
You want to find a spanning tree of this graph which connects all vertices and has the least weight (i.e. the sum of weights of edges is minimal).
A spanning tree is a set of edge... | ---
title
mst_prim
---
# Minimum spanning tree - Prim's algorithm
Given a weighted, undirected graph $G$ with $n$ vertices and $m$ edges.
You want to find a spanning tree of this graph which connects all vertices and has the least weight (i.e. the sum of weights of edges is minimal).
A spanning tree is a set of edge... | Minimum spanning tree - Prim's algorithm |
---
title
levit_algorithm
---
# D´Esopo-Pape algorithm
Given a graph with $n$ vertices and $m$ edges with weights $w_i$ and a starting vertex $v_0$.
The task is to find the shortest path from the vertex $v_0$ to every other vertex.
The algorithm from D´Esopo-Pape will work faster than [Dijkstra's algorithm](dijkstr... | ---
title
levit_algorithm
---
# D´Esopo-Pape algorithm
Given a graph with $n$ vertices and $m$ edges with weights $w_i$ and a starting vertex $v_0$.
The task is to find the shortest path from the vertex $v_0$ to every other vertex.
The algorithm from D´Esopo-Pape will work faster than [Dijkstra's algorithm](dijkstr... | D´Esopo-Pape algorithm |
---
title
- Original
---
# Second Best Minimum Spanning Tree
A Minimum Spanning Tree $T$ is a tree for the given graph $G$ which spans over all vertices of the given graph and has the minimum weight sum of all the edges, from all the possible spanning trees.
A second best MST $T'$ is a spanning tree, that has the s... | ---
title
- Original
---
# Second Best Minimum Spanning Tree
A Minimum Spanning Tree $T$ is a tree for the given graph $G$ which spans over all vertices of the given graph and has the minimum weight sum of all the edges, from all the possible spanning trees.
A second best MST $T'$ is a spanning tree, that has the s... | Second Best Minimum Spanning Tree |
---
title
assignment_mincostflow
---
# Solving assignment problem using min-cost-flow
The **assignment problem** has two equivalent statements:
- Given a square matrix $A[1..N, 1..N]$, you need to select $N$ elements in it so that exactly one element is selected in each row and column, and the sum of the values ... | ---
title
assignment_mincostflow
---
# Solving assignment problem using min-cost-flow
The **assignment problem** has two equivalent statements:
- Given a square matrix $A[1..N, 1..N]$, you need to select $N$ elements in it so that exactly one element is selected in each row and column, and the sum of the values ... | Solving assignment problem using min-cost-flow |
---
title
connected_components
---
# Search for connected components in a graph
Given an undirected graph $G$ with $n$ nodes and $m$ edges. We are required to find in it all the connected components, i.e, several groups of vertices such that within a group each vertex can be reached from another and no path exists b... | ---
title
connected_components
---
# Search for connected components in a graph
Given an undirected graph $G$ with $n$ nodes and $m$ edges. We are required to find in it all the connected components, i.e, several groups of vertices such that within a group each vertex can be reached from another and no path exists b... | Search for connected components in a graph |
---
title
rmq_linear
---
# Solve RMQ (Range Minimum Query) by finding LCA (Lowest Common Ancestor)
Given an array `A[0..N-1]`.
For each query of the form `[L, R]` we want to find the minimum in the array `A` starting from position `L` and ending with position `R`.
We will assume that the array `A` doesn't change in ... | ---
title
rmq_linear
---
# Solve RMQ (Range Minimum Query) by finding LCA (Lowest Common Ancestor)
Given an array `A[0..N-1]`.
For each query of the form `[L, R]` we want to find the minimum in the array `A` starting from position `L` and ending with position `R`.
We will assume that the array `A` doesn't change in ... | Solve RMQ (Range Minimum Query) by finding LCA (Lowest Common Ancestor) |
---
title
lca_linear_offline
---
# Lowest Common Ancestor - Tarjan's off-line algorithm
We have a tree $G$ with $n$ nodes and we have $m$ queries of the form $(u, v)$.
For each query $(u, v)$ we want to find the lowest common ancestor of the vertices $u$ and $v$, i.e. the node that is an ancestor of both $u$ and $v$... | ---
title
lca_linear_offline
---
# Lowest Common Ancestor - Tarjan's off-line algorithm
We have a tree $G$ with $n$ nodes and we have $m$ queries of the form $(u, v)$.
For each query $(u, v)$ we want to find the lowest common ancestor of the vertices $u$ and $v$, i.e. the node that is an ancestor of both $u$ and $v$... | Lowest Common Ancestor - Tarjan's off-line algorithm |
---
title
dijkstra_sparse
---
# Dijkstra on sparse graphs
For the statement of the problem, the algorithm with implementation and proof can be found on the article [Dijkstra's algorithm](dijkstra.md).
## Algorithm
We recall in the derivation of the complexity of Dijkstra's algorithm we used two factors:
the time o... | ---
title
dijkstra_sparse
---
# Dijkstra on sparse graphs
For the statement of the problem, the algorithm with implementation and proof can be found on the article [Dijkstra's algorithm](dijkstra.md).
## Algorithm
We recall in the derivation of the complexity of Dijkstra's algorithm we used two factors:
the time o... | Dijkstra on sparse graphs |
---
title
edmonds_karp
---
# Maximum flow - Ford-Fulkerson and Edmonds-Karp
The Edmonds-Karp algorithm is an implementation of the Ford-Fulkerson method for computing a maximal flow in a flow network.
## Flow network
First let's define what a **flow network**, a **flow**, and a **maximum flow** is.
A **network** ... | ---
title
edmonds_karp
---
# Maximum flow - Ford-Fulkerson and Edmonds-Karp
The Edmonds-Karp algorithm is an implementation of the Ford-Fulkerson method for computing a maximal flow in a flow network.
## Flow network
First let's define what a **flow network**, a **flow**, and a **maximum flow** is.
A **network** ... | Maximum flow - Ford-Fulkerson and Edmonds-Karp |
---
title
bfs
---
# Breadth-first search
Breadth first search is one of the basic and essential searching algorithms on graphs.
As a result of how the algorithm works, the path found by breadth first search to any node is the shortest path to that node, i.e the path that contains the smallest number of edges in unw... | ---
title
bfs
---
# Breadth-first search
Breadth first search is one of the basic and essential searching algorithms on graphs.
As a result of how the algorithm works, the path found by breadth first search to any node is the shortest path to that node, i.e the path that contains the smallest number of edges in unw... | Breadth-first search |
---
title: Lowest Common Ancestor - O(sqrt(N)) and O(log N) with O(N) preprocessing
title
lca
---
# Lowest Common Ancestor - $O(\sqrt{N})$ and $O(\log N)$ with $O(N)$ preprocessing
Given a tree $G$. Given queries of the form $(v_1, v_2)$, for each query you need to find the lowest common ancestor (or least common anc... | ---
title: Lowest Common Ancestor - O(sqrt(N)) and O(log N) with O(N) preprocessing
title
lca
---
# Lowest Common Ancestor - $O(\sqrt{N})$ and $O(\log N)$ with $O(N)$ preprocessing
Given a tree $G$. Given queries of the form $(v_1, v_2)$, for each query you need to find the lowest common ancestor (or least common anc... | Lowest Common Ancestor - $O(\sqrt{N})$ and $O(\log N)$ with $O(N)$ preprocessing |
---
title: Finding articulation points in a graph in O(N+M)
title
cutpoints
---
# Finding articulation points in a graph in $O(N+M)$
We are given an undirected graph. An articulation point (or cut vertex) is defined as a vertex which, when removed along with associated edges, makes the graph disconnected (or more pre... | ---
title: Finding articulation points in a graph in O(N+M)
title
cutpoints
---
# Finding articulation points in a graph in $O(N+M)$
We are given an undirected graph. An articulation point (or cut vertex) is defined as a vertex which, when removed along with associated edges, makes the graph disconnected (or more pre... | Finding articulation points in a graph in $O(N+M)$ |
---
title
preflow_push_faster
---
# Maximum flow - Push-relabel method improved
We will modify the [push-relabel method](push-relabel.md) to achieve a better runtime.
## Description
The modification is extremely simple:
In the previous article we chosen a vertex with excess without any particular rule.
But it turn... | ---
title
preflow_push_faster
---
# Maximum flow - Push-relabel method improved
We will modify the [push-relabel method](push-relabel.md) to achieve a better runtime.
## Description
The modification is extremely simple:
In the previous article we chosen a vertex with excess without any particular rule.
But it turn... | Maximum flow - Push-relabel method improved |
---
title
ford_bellman
---
# Bellman-Ford Algorithm
**Single source shortest path with negative weight edges**
Suppose that we are given a weighted directed graph $G$ with $n$ vertices and $m$ edges, and some specified vertex $v$. You want to find the length of shortest paths from vertex $v$ to every other vertex.
... | ---
title
ford_bellman
---
# Bellman-Ford Algorithm
**Single source shortest path with negative weight edges**
Suppose that we are given a weighted directed graph $G$ with $n$ vertices and $m$ edges, and some specified vertex $v$. You want to find the length of shortest paths from vertex $v$ to every other vertex.
... | Bellman-Ford Algorithm |
---
title
- Original
---
# 0-1 BFS
It is well-known, that you can find the shortest paths between a single source and all other vertices in $O(|E|)$ using [Breadth First Search](breadth-first-search.md) in an **unweighted graph**, i.e. the distance is the minimal number of edges that you need to traverse from the s... | ---
title
- Original
---
# 0-1 BFS
It is well-known, that you can find the shortest paths between a single source and all other vertices in $O(|E|)$ using [Breadth First Search](breadth-first-search.md) in an **unweighted graph**, i.e. the distance is the minimal number of edges that you need to traverse from the s... | 0-1 BFS |
---
title
heavy_light
---
# Heavy-light decomposition
**Heavy-light decomposition** is a fairly general technique that allows us to effectively solve many problems that come down to **queries on a tree** .
## Description
Let there be a tree $G$ of $n$ vertices, with an arbitrary root.
The essence of this tree de... | ---
title
heavy_light
---
# Heavy-light decomposition
**Heavy-light decomposition** is a fairly general technique that allows us to effectively solve many problems that come down to **queries on a tree** .
## Description
Let there be a tree $G$ of $n$ vertices, with an arbitrary root.
The essence of this tree de... | Heavy-light decomposition |
---
title
lca_simpler
---
# Lowest Common Ancestor - Binary Lifting
Let $G$ be a tree.
For every query of the form `(u, v)` we want to find the lowest common ancestor of the nodes `u` and `v`, i.e. we want to find a node `w` that lies on the path from `u` to the root node, that lies on the path from `v` to the root ... | ---
title
lca_simpler
---
# Lowest Common Ancestor - Binary Lifting
Let $G$ be a tree.
For every query of the form `(u, v)` we want to find the lowest common ancestor of the nodes `u` and `v`, i.e. we want to find a node `w` that lies on the path from `u` to the root node, that lies on the path from `v` to the root ... | Lowest Common Ancestor - Binary Lifting |
---
title
min_cost_flow
---
# Minimum-cost flow - Successive shortest path algorithm
Given a network $G$ consisting of $n$ vertices and $m$ edges.
For each edge (generally speaking, oriented edges, but see below), the capacity (a non-negative integer) and the cost per unit of flow along this edge (some integer) are ... | ---
title
min_cost_flow
---
# Minimum-cost flow - Successive shortest path algorithm
Given a network $G$ consisting of $n$ vertices and $m$ edges.
For each edge (generally speaking, oriented edges, but see below), the capacity (a non-negative integer) and the cost per unit of flow along this edge (some integer) are ... | Minimum-cost flow - Successive shortest path algorithm |
---
title
bipartite_checking
---
# Check whether a graph is bipartite
A bipartite graph is a graph whose vertices can be divided into two disjoint sets so that every edge connects two vertices from different sets (i.e. there are no edges which connect vertices from the same set). These sets are usually called sides.... | ---
title
bipartite_checking
---
# Check whether a graph is bipartite
A bipartite graph is a graph whose vertices can be divided into two disjoint sets so that every edge connects two vertices from different sets (i.e. there are no edges which connect vertices from the same set). These sets are usually called sides.... | Check whether a graph is bipartite |
---
title
2_sat
---
# 2-SAT
SAT (Boolean satisfiability problem) is the problem of assigning Boolean values to variables to satisfy a given Boolean formula.
The Boolean formula will usually be given in CNF (conjunctive normal form), which is a conjunction of multiple clauses, where each clause is a disjunction of l... | ---
title
2_sat
---
# 2-SAT
SAT (Boolean satisfiability problem) is the problem of assigning Boolean values to variables to satisfy a given Boolean formula.
The Boolean formula will usually be given in CNF (conjunctive normal form), which is a conjunction of multiple clauses, where each clause is a disjunction of l... | 2-SAT |
---
title
kirchhoff_theorem
---
# Kirchhoff's theorem. Finding the number of spanning trees
Problem: You are given a connected undirected graph (with possible multiple edges) represented using an adjacency matrix. Find the number of different spanning trees of this graph.
The following formula was proven by Kirchho... | ---
title
kirchhoff_theorem
---
# Kirchhoff's theorem. Finding the number of spanning trees
Problem: You are given a connected undirected graph (with possible multiple edges) represented using an adjacency matrix. Find the number of different spanning trees of this graph.
The following formula was proven by Kirchho... | Kirchhoff's theorem. Finding the number of spanning trees |
---
title
- Original
---
# Strong Orientation
A **strong orientation** of an undirected graph is an assignment of a direction to each edge that makes it a [strongly connected graph](strongly-connected-components.md).
That is, after the *orientation* we should be able to visit any vertex from any vertex by following... | ---
title
- Original
---
# Strong Orientation
A **strong orientation** of an undirected graph is an assignment of a direction to each edge that makes it a [strongly connected graph](strongly-connected-components.md).
That is, after the *orientation* we should be able to visit any vertex from any vertex by following... | Strong Orientation |
---
title
mst_kruskal
---
# Minimum spanning tree - Kruskal's algorithm
Given a weighted undirected graph.
We want to find a subtree of this graph which connects all vertices (i.e. it is a spanning tree) and has the least weight (i.e. the sum of weights of all the edges is minimum) of all possible spanning trees.
Th... | ---
title
mst_kruskal
---
# Minimum spanning tree - Kruskal's algorithm
Given a weighted undirected graph.
We want to find a subtree of this graph which connects all vertices (i.e. it is a spanning tree) and has the least weight (i.e. the sum of weights of all the edges is minimum) of all possible spanning trees.
Th... | Minimum spanning tree - Kruskal's algorithm |
---
title
preflow_push
---
# Maximum flow - Push-relabel algorithm
The push-relabel algorithm (or also known as preflow-push algorithm) is an algorithm for computing the maximum flow of a flow network.
The exact definition of the problem that we want to solve can be found in the article [Maximum flow - Ford-Fulkerso... | ---
title
preflow_push
---
# Maximum flow - Push-relabel algorithm
The push-relabel algorithm (or also known as preflow-push algorithm) is an algorithm for computing the maximum flow of a flow network.
The exact definition of the problem that we want to solve can be found in the article [Maximum flow - Ford-Fulkerso... | Maximum flow - Push-relabel algorithm |
---
title: Checking a graph for acyclicity and finding a cycle in O(M)
title
finding_cycle
---
# Checking a graph for acyclicity and finding a cycle in $O(M)$
Consider a directed or undirected graph without loops and multiple edges. We have to check whether it is acyclic, and if it is not, then find any cycle.
We ca... | ---
title: Checking a graph for acyclicity and finding a cycle in O(M)
title
finding_cycle
---
# Checking a graph for acyclicity and finding a cycle in $O(M)$
Consider a directed or undirected graph without loops and multiple edges. We have to check whether it is acyclic, and if it is not, then find any cycle.
We ca... | Checking a graph for acyclicity and finding a cycle in $O(M)$ |
---
title: Finding bridges in a graph in O(N+M)
title
bridge_searching
---
# Finding bridges in a graph in $O(N+M)$
We are given an undirected graph. A bridge is defined as an edge which, when removed, makes the graph disconnected (or more precisely, increases the number of connected components in the graph). The tas... | ---
title: Finding bridges in a graph in O(N+M)
title
bridge_searching
---
# Finding bridges in a graph in $O(N+M)$
We are given an undirected graph. A bridge is defined as an edge which, when removed, makes the graph disconnected (or more precisely, increases the number of connected components in the graph). The tas... | Finding bridges in a graph in $O(N+M)$ |
---
title
mst_kruskal_with_dsu
---
# Minimum spanning tree - Kruskal with Disjoint Set Union
For an explanation of the MST problem and the Kruskal algorithm, first see the [main article on Kruskal's algorithm](mst_kruskal.md).
In this article we will consider the data structure ["Disjoint Set Union"](../data_struct... | ---
title
mst_kruskal_with_dsu
---
# Minimum spanning tree - Kruskal with Disjoint Set Union
For an explanation of the MST problem and the Kruskal algorithm, first see the [main article on Kruskal's algorithm](mst_kruskal.md).
In this article we will consider the data structure ["Disjoint Set Union"](../data_struct... | Minimum spanning tree - Kruskal with Disjoint Set Union |
---
title
lca_linear
---
# Lowest Common Ancestor - Farach-Colton and Bender Algorithm
Let $G$ be a tree.
For every query of the form $(u, v)$ we want to find the lowest common ancestor of the nodes $u$ and $v$, i.e. we want to find a node $w$ that lies on the path from $u$ to the root node, that lies on the path fr... | ---
title
lca_linear
---
# Lowest Common Ancestor - Farach-Colton and Bender Algorithm
Let $G$ be a tree.
For every query of the form $(u, v)$ we want to find the lowest common ancestor of the nodes $u$ and $v$, i.e. we want to find a node $w$ that lies on the path from $u$ to the root node, that lies on the path fr... | Lowest Common Ancestor - Farach-Colton and Bender Algorithm |
---
title
floyd_warshall_algorithm
---
# Floyd-Warshall Algorithm
Given a directed or an undirected weighted graph $G$ with $n$ vertices.
The task is to find the length of the shortest path $d_{ij}$ between each pair of vertices $i$ and $j$.
The graph may have negative weight edges, but no negative weight cycles.
... | ---
title
floyd_warshall_algorithm
---
# Floyd-Warshall Algorithm
Given a directed or an undirected weighted graph $G$ with $n$ vertices.
The task is to find the length of the shortest path $d_{ij}$ between each pair of vertices $i$ and $j$.
The graph may have negative weight edges, but no negative weight cycles.
... | Floyd-Warshall Algorithm |
---
title
assignment_mincostflow
---
# Solving assignment problem using min-cost-flow
The **assignment problem** has two equivalent statements:
- Given a square matrix $A[1..N, 1..N]$, you need to select $N$ elements in it so that exactly one element is selected in each row and column, and the sum of the values ... | ---
title
assignment_mincostflow
---
# Solving assignment problem using min-cost-flow
The **assignment problem** has two equivalent statements:
- Given a square matrix $A[1..N, 1..N]$, you need to select $N$ elements in it so that exactly one element is selected in each row and column, and the sum of the values ... | Solving assignment problem using min-cost-flow |
---
title
bfs
---
# Breadth-first search
Breadth first search is one of the basic and essential searching algorithms on graphs.
As a result of how the algorithm works, the path found by breadth first search to any node is the shortest path to that node, i.e the path that contains the smallest number of edges in unw... | ---
title
bfs
---
# Breadth-first search
Breadth first search is one of the basic and essential searching algorithms on graphs.
As a result of how the algorithm works, the path found by breadth first search to any node is the shortest path to that node, i.e the path that contains the smallest number of edges in unw... | Breadth-first search |
---
title
johnson_problem_2
---
# Scheduling jobs on two machines
This task is about finding an optimal schedule for $n$ jobs on two machines.
Every item must first be processed on the first machine, and afterwards on the second one.
The $i$-th job takes $a_i$ time on the first machine, and $b_i$ time on the second ... | ---
title
johnson_problem_2
---
# Scheduling jobs on two machines
This task is about finding an optimal schedule for $n$ jobs on two machines.
Every item must first be processed on the first machine, and afterwards on the second one.
The $i$-th job takes $a_i$ time on the first machine, and $b_i$ time on the second ... | Scheduling jobs on two machines |
---
title
schedule_with_completion_duration
---
# Optimal schedule of jobs given their deadlines and durations
Suppose, we have a set of jobs, and we are aware of every job’s deadline and its duration. The execution of a job cannot be interrupted prior to its ending. It is required to create such a schedule to accom... | ---
title
schedule_with_completion_duration
---
# Optimal schedule of jobs given their deadlines and durations
Suppose, we have a set of jobs, and we are aware of every job’s deadline and its duration. The execution of a job cannot be interrupted prior to its ending. It is required to create such a schedule to accom... | Optimal schedule of jobs given their deadlines and durations |
---
title
johnson_problem_1
---
# Scheduling jobs on one machine
This task is about finding an optimal schedule for $n$ jobs on a single machine, if the job $i$ can be processed in $t_i$ time, but for the $t$ seconds waiting before processing the job a penalty of $f_i(t)$ has to be paid.
Thus the task asks to find ... | ---
title
johnson_problem_1
---
# Scheduling jobs on one machine
This task is about finding an optimal schedule for $n$ jobs on a single machine, if the job $i$ can be processed in $t_i$ time, but for the $t$ seconds waiting before processing the job a penalty of $f_i(t)$ has to be paid.
Thus the task asks to find ... | Scheduling jobs on one machine |
---
title
binomial_coeff
---
# Binomial Coefficients
Binomial coefficients $\binom n k$ are the number of ways to select a set of $k$ elements from $n$ different elements without taking into account the order of arrangement of these elements (i.e., the number of unordered sets).
Binomial coefficients are also the c... | ---
title
binomial_coeff
---
# Binomial Coefficients
Binomial coefficients $\binom n k$ are the number of ways to select a set of $k$ elements from $n$ different elements without taking into account the order of arrangement of these elements (i.e., the number of unordered sets).
Binomial coefficients are also the c... | Binomial Coefficients |
---
title
inclusion_exclusion_principle
---
# The Inclusion-Exclusion Principle
The inclusion-exclusion principle is an important combinatorial way to compute the size of a set or the probability of complex events. It relates the sizes of individual sets with their union.
## Statement
### The verbal formula
The i... | ---
title
inclusion_exclusion_principle
---
# The Inclusion-Exclusion Principle
The inclusion-exclusion principle is an important combinatorial way to compute the size of a set or the probability of complex events. It relates the sizes of individual sets with their union.
## Statement
### The verbal formula
The i... | The Inclusion-Exclusion Principle |
---
title: Generating all K-combinations
title
generating_combinations
---
# Generating all $K$-combinations
In this article we will discuss the problem of generating all $K$-combinations.
Given the natural numbers $N$ and $K$, and considering a set of numbers from $1$ to $N$.
The task is to derive all **subsets of s... | ---
title: Generating all K-combinations
title
generating_combinations
---
# Generating all $K$-combinations
In this article we will discuss the problem of generating all $K$-combinations.
Given the natural numbers $N$ and $K$, and considering a set of numbers from $1$ to $N$.
The task is to derive all **subsets of s... | Generating all $K$-combinations |
---
title
bishops_arrangement
---
# Placing Bishops on a Chessboard
Find the number of ways to place $K$ bishops on an $N \times N$ chessboard so that no two bishops attack each other.
## Algorithm
This problem can be solved using dynamic programming.
Let's enumerate the diagonals of the chessboard as follows: bl... | ---
title
bishops_arrangement
---
# Placing Bishops on a Chessboard
Find the number of ways to place $K$ bishops on an $N \times N$ chessboard so that no two bishops attack each other.
## Algorithm
This problem can be solved using dynamic programming.
Let's enumerate the diagonals of the chessboard as follows: bl... | Placing Bishops on a Chessboard |
---
title
catalan_numbers
---
# Catalan Numbers
Catalan numbers is a number sequence, which is found useful in a number of combinatorial problems, often involving recursively-defined objects.
This sequence was named after the Belgian mathematician [Catalan](https://en.wikipedia.org/wiki/Eug%C3%A8ne_Charles_Catalan),... | ---
title
catalan_numbers
---
# Catalan Numbers
Catalan numbers is a number sequence, which is found useful in a number of combinatorial problems, often involving recursively-defined objects.
This sequence was named after the Belgian mathematician [Catalan](https://en.wikipedia.org/wiki/Eug%C3%A8ne_Charles_Catalan),... | Catalan Numbers |
---
title
burnside_polya
---
# Burnside's lemma / Pólya enumeration theorem
## Burnside's lemma
**Burnside's lemma** was formulated and proven by **Burnside** in 1897, but historically it was already discovered in 1887 by **Frobenius**, and even earlier in 1845 by **Cauchy**.
Therefore it is also sometimes named th... | ---
title
burnside_polya
---
# Burnside's lemma / Pólya enumeration theorem
## Burnside's lemma
**Burnside's lemma** was formulated and proven by **Burnside** in 1897, but historically it was already discovered in 1887 by **Frobenius**, and even earlier in 1845 by **Cauchy**.
Therefore it is also sometimes named th... | Burnside's lemma / Pólya enumeration theorem |
---
title
counting_connected_graphs
---
# Counting labeled graphs
## Labeled graphs
Let the number of vertices in a graph be $n$.
We have to compute the number $G_n$ of labeled graphs with $n$ vertices (labeled means that the vertices are marked with the numbers from $1$ to $n$).
The edges of the graphs are conside... | ---
title
counting_connected_graphs
---
# Counting labeled graphs
## Labeled graphs
Let the number of vertices in a graph be $n$.
We have to compute the number $G_n$ of labeled graphs with $n$ vertices (labeled means that the vertices are marked with the numbers from $1$ to $n$).
The edges of the graphs are conside... | Counting labeled graphs |
---
title
bracket_sequences
---
# Balanced bracket sequences
A **balanced bracket sequence** is a string consisting of only brackets, such that this sequence, when inserted certain numbers and mathematical operations, gives a valid mathematical expression.
Formally you can define balanced bracket sequence with:
- $... | ---
title
bracket_sequences
---
# Balanced bracket sequences
A **balanced bracket sequence** is a string consisting of only brackets, such that this sequence, when inserted certain numbers and mathematical operations, gives a valid mathematical expression.
Formally you can define balanced bracket sequence with:
- $... | Balanced bracket sequences |
---
title
- Original
---
# Stars and bars
Stars and bars is a mathematical technique for solving certain combinatorial problems.
It occurs whenever you want to count the number of ways to group identical objects.
## Theorem
The number of ways to put $n$ identical objects into $k$ labeled boxes is
$$\binom{n + k ... | ---
title
- Original
---
# Stars and bars
Stars and bars is a mathematical technique for solving certain combinatorial problems.
It occurs whenever you want to count the number of ways to group identical objects.
## Theorem
The number of ways to put $n$ identical objects into $k$ labeled boxes is
$$\binom{n + k ... | Stars and bars |
# Garner's algorithm
A consequence of the [Chinese Remainder Theorem](chinese-remainder-theorem.md) is, that we can represent big numbers using an array of small integers.
For example, let $p$ be the product of the first $1000$ primes. $p$ has around $3000$ digits.
Any number $a$ less than $p$ can be represented as a... | # Garner's algorithm
A consequence of the [Chinese Remainder Theorem](chinese-remainder-theorem.md) is, that we can represent big numbers using an array of small integers.
For example, let $p$ be the product of the first $1000$ primes. $p$ has around $3000$ digits.
Any number $a$ less than $p$ can be represented as a... | Garner's algorithm |
---
title
factorial_divisors
---
# Finding Power of Factorial Divisor
You are given two numbers $n$ and $k$. Find the largest power of $k$ $x$ such that $n!$ is divisible by $k^x$.
## Prime $k$ {data-toc-label="Prime k"}
Let's first consider the case of prime $k$. The explicit expression for factorial
$$n! = 1 \c... | ---
title
factorial_divisors
---
# Finding Power of Factorial Divisor
You are given two numbers $n$ and $k$. Find the largest power of $k$ $x$ such that $n!$ is divisible by $k^x$.
## Prime $k$ {data-toc-label="Prime k"}
Let's first consider the case of prime $k$. The explicit expression for factorial
$$n! = 1 \c... | Finding Power of Factorial Divisor |
---
title
- Original
---
# Operations on polynomials and series
Problems in competitive programming, especially the ones involving enumeration some kind, are often solved by reducing the problem to computing something on polynomials and formal power series.
This includes concepts such as polynomial multiplication,... | ---
title
- Original
---
# Operations on polynomials and series
Problems in competitive programming, especially the ones involving enumeration some kind, are often solved by reducing the problem to computing something on polynomials and formal power series.
This includes concepts such as polynomial multiplication,... | Operations on polynomials and series |
---
title
eratosthenes_sieve
---
# Sieve of Eratosthenes
Sieve of Eratosthenes is an algorithm for finding all the prime numbers in a segment $[1;n]$ using $O(n \log \log n)$ operations.
The algorithm is very simple:
at the beginning we write down all numbers between 2 and $n$.
We mark all proper multiples of 2 (si... | ---
title
eratosthenes_sieve
---
# Sieve of Eratosthenes
Sieve of Eratosthenes is an algorithm for finding all the prime numbers in a segment $[1;n]$ using $O(n \log \log n)$ operations.
The algorithm is very simple:
at the beginning we write down all numbers between 2 and $n$.
We mark all proper multiples of 2 (si... | Sieve of Eratosthenes |
---
title
binary_pow
---
# Binary Exponentiation
Binary exponentiation (also known as exponentiation by squaring) is a trick which allows to calculate $a^n$ using only $O(\log n)$ multiplications (instead of $O(n)$ multiplications required by the naive approach).
It also has important applications in many tasks unr... | ---
title
binary_pow
---
# Binary Exponentiation
Binary exponentiation (also known as exponentiation by squaring) is a trick which allows to calculate $a^n$ using only $O(\log n)$ multiplications (instead of $O(n)$ multiplications required by the naive approach).
It also has important applications in many tasks unr... | Binary Exponentiation |
---
title
balanced_ternary
---
# Balanced Ternary

This is a non-standard but still positional **numeral system**. Its feature is that digits can have one of the values `-1`, `0` and `1`.
Nevertheles... | ---
title
balanced_ternary
---
# Balanced Ternary

This is a non-standard but still positional **numeral system**. Its feature is that digits can have one of the values `-1`, `0` and `1`.
Nevertheles... | Balanced Ternary |
---
title
discrete_root
---
# Discrete Root
The problem of finding a discrete root is defined as follows. Given a prime $n$ and two integers $a$ and $k$, find all $x$ for which:
$x^k \equiv a \pmod n$
## The algorithm
We will solve this problem by reducing it to the [discrete logarithm problem](discrete-log.md).
... | ---
title
discrete_root
---
# Discrete Root
The problem of finding a discrete root is defined as follows. Given a prime $n$ and two integers $a$ and $k$, find all $x$ for which:
$x^k \equiv a \pmod n$
## The algorithm
We will solve this problem by reducing it to the [discrete logarithm problem](discrete-log.md).
... | Discrete Root |
---
title
- Original
---
# Integer factorization
In this article we list several algorithms for factorizing integers, each of them can be both fast and also slow (some slower than others) depending on their input.
Notice, if the number that you want to factorize is actually a prime number, most of the algorithms, ... | ---
title
- Original
---
# Integer factorization
In this article we list several algorithms for factorizing integers, each of them can be both fast and also slow (some slower than others) depending on their input.
Notice, if the number that you want to factorize is actually a prime number, most of the algorithms, ... | Integer factorization |
---
title
all_submasks
---
# Submask Enumeration
## Enumerating all submasks of a given mask
Given a bitmask $m$, you want to efficiently iterate through all of its submasks, that is, masks $s$ in which only bits that were included in mask $m$ are set.
Consider the implementation of this algorithm, based on tricks... | ---
title
all_submasks
---
# Submask Enumeration
## Enumerating all submasks of a given mask
Given a bitmask $m$, you want to efficiently iterate through all of its submasks, that is, masks $s$ in which only bits that were included in mask $m$ are set.
Consider the implementation of this algorithm, based on tricks... | Submask Enumeration |
---
title
- Original
---
<!--?title Continued fractions -->
# Continued fractions
**Continued fraction** is a representation of a real number as a specific convergent sequence of rational numbers. They are useful in competitive programming because they are easy to compute and can be efficiently used to find the bes... | ---
title
- Original
---
<!--?title Continued fractions -->
# Continued fractions
**Continued fraction** is a representation of a real number as a specific convergent sequence of rational numbers. They are useful in competitive programming because they are easy to compute and can be efficiently used to find the bes... | Continued fractions |
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