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

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

Exact and meta-heuristic algorithms for NP problems

The Swiss Army Knife of Applied Quantum Technology (Experimental Tech)

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

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

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

A Reduced-order Binary Decision Diagram (RoBDD) SAT solver written in Rust

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).

Problem Solving: A Practical Workbook