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Performance evaluation of an improved hybrid genetic scatter search (IHGSS) algorithm for multistage hybrid flow shop scheduling problems with missing operations

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  • M.K. Marichelvam
  • T. Prabaharan

Abstract

Multistage hybrid flow shop scheduling problems are considered in this paper. Each stage consists of several identical machines. The jobs are to be processed on any one of the machines at each stage. In most of the scheduling research works it is assumed that all jobs are to be processed at all stages. But in real-life industries some of the jobs may not be processed at some stages. Hence hybrid flow shop scheduling problems with missing operations are considered in this paper with the objective of determining a schedule that minimises makespan. The hybrid flow shop scheduling problems are non-deterministic polynomial time hard (NP-hard) problems. We propose a hybrid meta-heuristic algorithm, namely improved hybrid genetic scatter search (IHGSS) algorithm, based on genetic algorithm and scatter search algorithms. A case study problem of a leading steel furniture manufacturing company in India is presented to illustrate the proposed algorithm. Computational experiments show that the proposed IHGSS algorithm outperforms other heuristic and meta-heuristic algorithms.

Suggested Citation

  • M.K. Marichelvam & T. Prabaharan, 2014. "Performance evaluation of an improved hybrid genetic scatter search (IHGSS) algorithm for multistage hybrid flow shop scheduling problems with missing operations," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 16(1), pages 120-141.
    • Handle: RePEc:ids:ijisen:v:16:y:2014:i:1:p:120-141
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    Cited by:

    1. Hongtao Tang & Jiahao Zhou & Yiping Shao & Zhixiong Yang, 2023. "Hybrid Flow-Shop Scheduling Problems with Missing and Re-Entrant Operations Considering Process Scheduling and Production of Energy Consumption," Sustainability, MDPI, vol. 15(10), pages 1-19, May.

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