/metaheuristics-tutorial

Metaheuristics using Python

Primary LanguagePython

Python37 Version Kyungsu

metaheuristics-tutorial

Please do not refer to this code until Nov. 2019.

metaheuristics-tutorial is a tutorial for who is studying metaheuristics, combinatorial optimization, operations research using Python, DEAP (Distributed Evolutionary Algorithms in Python).

Dependencies

metaheuristics-tutorial requires:

  • Python (>= 3.7.4)
  • NumPy (>= 1.16.5)
  • pandas (>= 0.25.1)
  • SciPy (>= 0.17.0)
  • PuLP (>= 1.6.9)
  • DEAP (>= 1.3.1)
  • tabulate (>= 0.8.5)

metaheuristics-tutoral does not support Python 2.7.

Combinatorial Optimization using Metaheuristics

Problems

  1. Travelling Salesman Problem
  2. Knapsack Problem

Simulated Annealing (SA)

  1. Description
  2. Materials
    • Paper -
  3. Continuous -
  4. Discrete -

Tabu Search (TS)

  1. Description
  2. Materials
    • Paper -
  3. Discrete

Genetic Algorithm (GA)

  1. Materials
    • Paper -
  2. Continuous -
  3. Discrete -

Evolution Strategy (ES)

  1. Materials
    • Paper -
  2. Continuous -

Particle Swarm Optimization (PSO)

  1. Materials
    • Paper -
  2. Continuous -
  3. Discrete -

Ant Colony Optimization (ACO)

  1. Materials
    • Paper -
  2. Discrete -

Changelog