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Python implementation of a genetic algorithm for FJSP.

Based on a paper written by Xinyu Li and Liang Gao [1].

Code structure

The code has been designed to be read along the section 4 of this paper.

  • Workflow of the proposed HA (4.1)
    • main.py
  • Encoding and decoding (4.2)
    • encoding.py, decoding.py
  • Genetic operators (4.3)
    • genetic.py
  • Local search by tabu search (4.4)
    • This section has been ignored
  • Terminate criteria (4.5)
    • termination.py

Usage

To run the algorithm on the Mk02 problem from the Brandimarte data:

$ python3 main.py test_data/Brandimarte_Data/Text/Mk02.fjs

Test data can be found on this site.

References

[1] Xinyu Li and Liang Gao. An effective hybrid genetic algorithm and tabu searchfor flexible job shop scheduling problem.International Journal of ProductionEconomics, 174 :93 – 110, 2016