Welcome to the jungle

Project of my internship at LERIA

Objectives:

- Implement bGWO, SLMS
  - A binary grey wolf optimizer for the multidimensional knapsack problem
    (Kaiping Luo, Qiuhong Zhao)
  - A binary moth search algorithm based on self-learning for multidimensional knapsack problems  
    (Yanhong Feng, Gai-Ge Wang)

- Develop a kind of general metaheuristics algorithm from those

TODO

• General algorithm
• Clean all files and add docstrings & comments

DOING

• General algorithm
  • Get a framework working
  • (optionnal) make it with the deap library
    • Make MKP model

DONE

• Implementation of the Multi dimensional Knapsack Problem

  • Initialization of instances
  • Model
  • Fitness function
  • Pseudo utility

• bGWO

  • Make an algorithm from scratch
    • Initialisation pseudo utility
    • Initialisation 0
    • Initialisation random
    • Identify leaders (init)
    • Estimate the position of the prey (selection part 1 ?)
    • Generate solution (selection)
    • Repair (mutate)
    • Update population (Insertion)
    • Frame
  • find where to generalize

• SLMS

  • Make an algorithm from scratch
  • Initialisation random
  • Generate initial solution
  • Generate solution
    • Repair
  • find where to generalize

• PSO

  • Make a simple PSO
    • Modify it to try to get better results
    • Use parts of metaphor based algorithm to make a general pso algorithm resembling both gwo & slms
      • use different formulas
      • Change the framework of the pso to look like gwo & slms

Dependencies

• numpy
• scipy

See requirements.txt

Launch

\TODO