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Parallel Tabu Search and Genetic Algorithm for the Job Shop Schedule Problem with Sequence Dependent Set Up Times

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Job Shop Schedule Problem (JSSP)

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Version 2.1.0

JSSP is an optimization package for the Job Shop Schedule Problem.
JSSP has two different optimization algorithms:

  • Parallel Tabu Search
  • Genetic Algorithm

Features

  1. Find near optimal solutions to flexible job shop schedule problems with sequence dependency setup times.
  2. Use of Cython C extensions for fast execution of code.
  3. Plot tabu search and/or genetic algorithm optimization using Plotly.
  4. Create gantt charts using Plotly.
  5. Create production schedule excel file.

For more information as well as examples, read the docs.

How to Install

After cloning this repo, change directories to where setup.py exists and run

pip install --upgrade pip
pip install -r requirements.txt
pip install .

If you get an error about python.h not being found try installing python3-dev.

To build the C-extensions (i.e compile .pyx files) without installing JSSP run

python setup.py build_ext

How to Use

After installation, JSSP can imported as a normal python module.
For examples on how to use JSSP see the jupyter notebooks in the examples folder or see the docs.

Important Note

Job-Tasks in jobTasks.csv and sequenceDependencyMatrix.csv need to be in ascending order according to (job_id, task_id).

Example

The following example minimally demonstrates how to run parallel tabu search to find a solution to the problem instance in data/given_data.

from JSSP.solver import Solver
from JSSP.data import SpreadsheetData

# initialize data
data = SpreadsheetData('data/given_data/sequenceDependencyMatrix.csv',
                       'data/given_data/machineRunSpeed.csv',
                       'data/given_data/jobTasks.csv')

# run parallel Tabu Search
solver = Solver(data)
solution = solver.tabu_search_iter(iterations=500,
                                   num_processes=4,
                                   tabu_list_size=20,
                                   neighborhood_size=250)

# create Schedule
solution.create_schedule_xlsx_file('output/Schedule.xlsx')                   

Flexible Job Shop

To read in a flexible job shop problem instance from a .fjs file (see data/fjs_data) do the following:

from JSSP.data import FJSData

data = FJSData('data/fjs_data/Barnes/Barnes_mt10c1.fjs')

How to Contribute

If you would like to contribute to this project please see CONTRIBUTING.md.

License

JSSP is licensed under the ISC License:

ISC License

Copyright (c) 2019, Matthew McFadden

Permission to use, copy, modify, and/or distribute this software for any
purpose with or without fee is hereby granted, provided that the above
copyright notice and this permission notice appear in all copies.

THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.