🗺️ Visualize and control algorithms for the traveling salesman problem
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Updated
Oct 30, 2024 - JavaScript
🗺️ Visualize and control algorithms for the traveling salesman problem
Tries to create a list of popular movies based on a series of heuristics
A python library with implementations of 15 classical heuristics for the capacitated vehicle routing problem.
a python grammar for evolutionary algorithms and heuristics
A 2D/3D visualization of the Traveling Salesman Problem main heuristics
SparklingGraph provides easy to use set of features that will give you ability to proces large scala graphs using Spark and GraphX.
Coursera's Data Structures and Algorithms Specialization
An asychronous A* pathfinding library for serverside minecraft development
A MSc's Dissertation Project which focuses on Vehicle Routing Problem with Time Windows (VRPTW), using both exact method and heuristic approach (General Variable Neighbourhood Search)
Heuristics for software design, development, testing, and maintenance programming.
Program for managing orders, planning and scheduling in job shop production system using popular heuristics alghorithms.
Next-generation firewall (NGFW) that supports blocking SocialClub Overlay notifications.
An improvement-based Deep Reinforcement Learning Algorithm presented in paper https://arxiv.org/abs/1912.05784v2 for solving the TSP problem.
Humble 3D knapsack / bin packing solver
OptFrame - C++17 (and C++20) Optimization Framework in Single or Multi-Objective. Supports classic metaheuristics and hyperheuristics: Genetic Algorithm, Simulated Annealing, Tabu Search, Iterated Local Search, Variable Neighborhood Search, NSGA-II, Genetic Programming etc. Examples for Traveling Salesman, Vehicle Routing, Knapsack Problem, etc.
Some usefull info when reverse engineering Kernel Mode Anti-Cheat
ALNS header-only library (loosely) based on the original implementation by Stefan Ropke.
A Pytorch implementation of Generative Adversarial Network for Heuristics of Sampling-based Path Planning
Job Shop Scheduling Problem via Ant Colony Optimization
The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, three main steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented to perform optim…
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