MetaHeuristics

Metaheuristics implemented

• Genetic Algorithm (GA)
• Local Search (SL)
• Iterated Local Search (ILS)
• Population Base Incremental Learning (PBIL)
• Simulated Annealing (SA)
• Tabu Search (TS)
• Artificial Bee Colony (ABC)

Knapsack Problem

  python main_KSP.py

Knapsack Problem performance

  python main_statis_KSP.py

1D function Problem

  python main.py

1D function Problem performance

  python main_statis.py

Biography

• Simulated annealing: From basics to applications (Daniel Delahaye, Supatcha Chaimatanan, Marcel Mongeau)
• Iterated Local Search: Framework and Applications (Helena Ramalhinho Lourenco, Thomas Stuzle, Olivier C Martin)
• An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics (Shumeet Baluja)
• An Efficient Algorithm for the Knapsack Sharing Problem (Mhand Hifi, Slim Sadfi, Abdelkader Shibi)
• An Overview of Genetic Algorithms: Part 1, Fundamentals (David Beasley, David R.Bull, Ralph R. Martin)
• Comparison of Metaheuristics (John Silberholz and Bruce Golden)
• Removing the Genetics from the Standard Genetic Algorithm
• Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems (Dervis Karaboga and Bahriye Basturk)

Biography not yet implemented

• Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem
• On the Neighborhood Structure of the Traveling Salesman Problem Generated by Local Search Moves (Günther Stattenberger, Markus Dankesreiter, Florian Baumgartner, Johannes J.Schneider)
• MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with time windows