AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.
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Updated
Nov 10, 2024 - Java
AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.
Search over large image datasets with natural language and computer vision!
OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.
Fast & Lightweight Zola Theme
A modern Zola theme with search, multilingual support, optional JavaScript, a perfect Lighthouse score, and a focus on accessibility.
Solving VRPTW with metaheuristics
A curated list of amazingly awesome local seo resources.
A Java library of Customizable, Hybridizable, Iterative, Parallel, Stochastic, and Self-Adaptive Local Search Algorithms
Amazing Collection Vehicle Routing Problem
Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). This repository mirrors https://gitlab.com/NMOF/NMOF .
Solver for Capacitance Vehicle Routing Problem - School bus routing problem with bus stop selection
A C# Library to aid programming for meta-heuristics
A Julia package to manage Constraint-Based Local Search (CBLS) solvers.
A metaheuristic optimization framework
Java Constraint Solvers for Vehicle Routing Problem (VRP)
A Greedy Randomized Adaptive Search Procedure (GRASP) for the Traveling Salesman Problem (TSP)
The research work on Vehicle Routing Problem (VRP) solving via Artifical Bee colony algorithm
Python/Numba implemenation of of Lin-Kernighan-style TSP solver
🌱 Genetic Algorithm, Memetic Algorithms, GRASP, Simulated Annealing, Multi start search, Reiterated Local Search, Local Search, Greedy and randomized Greedy
This repository contains algorithms in C++ to solve the Capacitated Vehicle Routing Problem (cvrp).
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