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BFSP-DIWO

Project Overview

This project addresses a variant of the Flowshop scheduling problem—the Blocking Flow-Shop Scheduling Problem (BFSP).

  • Main algorithm: Discrete Invasive Weed Optimization (DIWO)
  • Implementation: C++ with large-scale testing support

Repository Structure

  • src/: C++ source code
  • data/NEH/: NEH algorithm and datasets
  • result/: Result output and processing
    • original/: Raw results, processing scripts
    • final/: Final aggregated data
  • LICENSE: License information
  • CMakeLists.txt: C++ build configuration

Usage

  1. Build:
mkdir build && cd build
cmake ..          
make              
  1. Runtime inputs:
  • n: Number of jobs
  • m: Number of machines
  • processingtime: Processing time matrix

References

  • Shao Z, Pi D, Shao W, et al. An efficient discrete invasive weed optimization for blocking flow-shop scheduling problem. Engineering Applications of Artificial Intelligence, 2019, 78: 124–141.
  • Wang L, Pan Q K, Suganthan P N, et al. A novel hybrid discrete differential evolution algorithm for blocking flow shop scheduling problems. Computers & Operations Research, 2010, 37(3): 509–520.
  • Pan Q K, Wang L. Effective heuristics for the blocking flowshop scheduling problem with makespan minimization. Omega, 2012, 40(2): 218–229.

LICENSE

  • This project is primarily licensed under the MIT License (see LICENSE in the root directory).

Change Log

  • 2024.07.31 Initial upload of NEH algorithm
  • 08.09 Updated RSB-PF_NEH, uploaded Alg1-NEH algorithm
  • 09.19 Uploaded NEH for reference
  • 10.04 Completed ALG1 modifications
  • 10.27 Uploaded ALG2
  • 11.20 Restructured project layout
  • 11.21 Completed ALG2 debugging
  • 11.22 Completed basic ALG3 implementation; computation speed can still be optimized
  • 11.22 Full implementation completed; bugs pending
  • 11.23 Bug fixes completed
  • 2025.01.16 Minor refinements
  • 03.23 Completed speed-up algorithm implementation
  • 04.26 Completed parameter tuning
  • 04.27 Project concluded!
  • 2026.4.2 Open source the codebase

Future Directions

  1. Attempt to improve the paper's algorithm
  2. Attempt to optimize algorithm time complexity

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