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Multi-criteria M-machine SDST flow shop scheduling using modified heuristic genetic algorithm

Author

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  • D. Satyanarayana
  • M. Pramiladevi

Abstract

The multi-criteria flow shop scheduling problem with sequence dependent setup times (SDST) is one of the most difficult class of scheduling problems. Efficient supervision of heuristics with SDST is one of the significant features to enhance the performance of manufacturing system. In this work, we have formulated multi-criteria decision-making flow shop scheduling problem. It consists of weighted sum of total weighted squared tardiness, makespan, total weighted squared earliness and number of tardy jobs. It is a very effective decision-making for scheduling jobs in modern manufacturing environment. In the present work, three efficient special heuristics based hybrid genetic algorithms (i.e., SHGA1, SHGA2, and SHGA3) are proposed for multi-criteria SDST. Experiments are conducted on the benchmark problems (Taillard, 1993). The performance of three SHGAs are tested, analysed and compared with the help of a defined performance index, known as relative percentage deviation (RPD). The maximum size of the problem is limited to 100 jobs and ten machines. From the results and analysis, the performance of SHGA3 found to be the best.

Suggested Citation

  • D. Satyanarayana & M. Pramiladevi, 2016. "Multi-criteria M-machine SDST flow shop scheduling using modified heuristic genetic algorithm," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 22(4), pages 409-422.
    • Handle: RePEc:ids:ijisen:v:22:y:2016:i:4:p:409-422
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