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Heuristic solver based on Ant Colony Optimization and designed for the Permutation Flow Shop Scheduling Problem with Weighted Tardiness (PFSP-WT)

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PFSP-WT

Ant Colony Optimization applied to the Permutation Flow-Show Problem with Weighted Tardiness. The software provides implementation of the MMAS, M-MMAS and PACO algorithms, as well as support for bi-objective optimization.

How to use it

The program can be called from the root of the project folder with a command of the form:

python run.py <path-to-instance> --method MMAS --time 30 --local-search swap --rho 0.4 --n-ants 40

where "method" can take the values "MMAS", "M-MMAS" and "PACO", "local-search" can take the values "swap", "interchange" or "insertion", rho is the pheromone trail persistence and n-ants is the number of ants in the colony.

For more command line arguments, simply type:

python run.py
  • "run.py" is the entry point of the program.
  • "hpo.py" is the script for hyper-optimizing the different algorithms.

Dependencies

NumPy, Numba

The project has been developped with the following versions:

  • numpy == 1.15.4
  • numba == 0.41.0

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Heuristic solver based on Ant Colony Optimization and designed for the Permutation Flow Shop Scheduling Problem with Weighted Tardiness (PFSP-WT)

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