AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.

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

A Java library of Customizable, Hybridizable, Iterative, Parallel, Stochastic, and Self-Adaptive Local Search Algorithms

Java Constraint Solvers for Vehicle Routing Problem (VRP)

The source code examples for the book "An Introduction to Optimization Algorithms"

local search and optimization algorithms are used in AI with a map coloring example | AI course - Fall 2018

JCOL: A Java package for solving the graph coloring problem (a heuristic)

The W-Model, a tunable Black-Box Discrete Optimization Benchmarking (BB-DOB) problem, implemented for the BB-DOB@GECCO Workshop.

Implementation of optimization algorithms to analyze the efficiency and effectiveness of said algorithms.

Practica 1 de metaheuristica

A classroom assignment with built-in, reverse, and search functions

This project presents a heuristic to solve a simplified version of the examination timetabling problem.

Assignments of artificial intelligent course

Mutant kill-based local search augmented evolutionary algorithm test case prioritization technique. (COMPSAC 2021)

Artificial Intelligence

Local Search Scheduling with Simulated Annealing

Package provides java implementation of local searchers in continuous and discrete optimization problems

🗺️ Local Search for Bicing (IA-FIB)

Vehicle Routing Problem, based on Greedy algorythm.