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