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!

Parallel Tabu Search and Genetic Algorithm for the Job Shop Schedule Problem with Sequence Dependent Set Up Times

Repository of scripts and data for the "Robustness and resilience of complex networks" paper by Oriol Artime, Marco Grassia, Manlio De Domenico, James P. Gleeson, Hernán A. Makse, Giuseppe Mangioni, Matjaž Perc and Filippo Radicchi, published at Nature Review Physics (2024). https://doi.org/10.1038/s42254-023-00676-y

Repository of the paper "Machine learning dismantling and early-warning signals of disintegration in complex systems" by M. Grassia, M. De Domenico and G. Mangioni

A List of Papers on Theoretical Foundations of Graph Neural Networks

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

[IEEE TKDE | TITS 2023] "Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling" | "Neural Airport Ground Handling"

A Python implementation of a branch-and-bound approach (plus a simple greedy heuristic) to solve a variation of the multiple knapsack problem where items have both individual and pairwise benefits.

Go (golang) bindings for Picosat, the satisfiability solver

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

Записките ми за упражнения по "Дизайн и анализ на алгоритми"

finding a short spanning walk throw a connected graph (NP-HARD problem)

A particle swarm optimization algorithm implementation with simultaneous pickup and drop for medicines distribution management.

Scala library for solving NP-hard probems

Feasibility Intensive Genetic Algorithm (FIGA) for the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW)

Official Implementation of the NeurIPS'23 paper 'Maximum Independent Set: Self-Training through Dynamic Programming'.

2017华为软件精英挑战赛，基于C++实现非JS

UAV path planning using Genetic Algorithm

My Edinburgh Napier University Honours Project: investigating the multi-objective Capacitated Vehicle Routing Problem with Time Windows (CVRPTW).

Optimized Delegated Byzantine Fault Tolerance

A hybrid genetic algorithm for the job shop scheduling problem

Part of the greedy algorithm used to solve the 2018 Alibaba Tianchi Competition-Server Dispatch Competition. This method ranks 66 in the preliminary round and is ranked second in the semi-finals. It is a good starting method.

Problem Solving: A Practical Workbook

GCS-Q is a coalition structure generation algorithm for induced subgraph games

A branch-and-bound, and A* type algorithm that solves the NP Hard Scheduling problem with the highest possible performance

Russian Doll Search for Computing Maximum Vertex Weight Hereditary Structures in Graphs. Now with OpenMP support.

Interactive travelling salesman problem solver. Branch & bound | Simulated annealing.

This repo encapsulates a Python implementation of the Simulated Annealing Algorithm to solve by means of a "minimum energy state" heuristic the NP-hard n-machines|no preemption|C_max job shop scheduling problem, considering n=2 machines and jobs having release dates. The code was designed and wrote by me. The whole heuristic design, complexity analysis, optimization, and ideas were made possible by team-working with Arianna Montironi and Chiara Panetta. The developed heuristic is the final deliverable of our project work held during the Quantitative Methods for Decision Aid 2021 Class in Politecnico di Torino.

The ripple-spreading algorithm for the k-color shortest path problem