OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.

Na Rinha de Algoritmos você deve utilizar suas habilidades para a criação de algoritmos eficientes para resolver problemas!

Experimental minisat SAT solver reimplementation in Rust

An Ant Colony Optimization algorithm for the Traveling Salesman Problem

A java implementation of the famous Lin-Kernighan heuristics algorithm implemented for graphic (symmetric) TSP

Exact and meta-heuristic algorithms for NP problems

Graph coloring problem solved with Genetic Algorithm, Tabu Search and Simulated Annealing

Python solutions for Tim Roughgarden's 4 part books called Algorithms Illuminated

Go (golang) bindings for Picosat, the satisfiability solver

🔎 wheeler graph recognition algorithm, visualization and generation

The Swiss Army Knife of Applied Quantum Technology

Implementation of classical problems in Computer Science in the Answer Set Solving dialect of Clingo.

Genetic algorithm to solve np-complete maximization problems. Originally intended for fantasy sports.

a collection of benchmarks (in DIMACS format) for various NP-Complete problems

Approximation Algorithm for the NP-Complete problem of finding a vertex cover of minimum weight in a graph with weighted vertices. Guarantees an answers at most 2 times the optimal minimum weighted vertex cover

Problem Solving: A Practical Workbook

https://portfolio.raghavkumar.co.in/collegeschduler Creates a college schedule using ant-colony optimisation to perform graph colouring. This was my sem 4 Software Engineering project

With this project we researched, implemented and analyzed different algorithms to effectively and efficiently solve an NP-Complete problem such as the Minimum Vertex Cover (MVC).

😆 Boolean formula satisfiability algorithms for JavaScript