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A New Approach for Solving the Flow Shop Scheduling Problem Through Neural Network Technique With Known Breakdown Time and Weights of Jobs

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  • Harendra Kumar

    (Gurukula Kangri Vishwavidyalaya, India)

  • Shailendra Giri

    (Gurukula Kangri Vishwavidyalaya, India)

Abstract

This paper considers a flow shop scheduling problems of n jobs on m machines involving processing times and weights of jobs with the major constraint as breakdown times of the machines. In this paper a new procedure is provided to obtain an optimal job sequence with the objective of minimize the makespan and mean weighted flow time by using neural network technique. To illustrate the proposed method procedure, a numerical example is given. The effectiveness of the proposed method is compared with many problems which are taken from different papers. This paper also provides a comparison of our proposed method with the existing methods in literature.

Suggested Citation

  • Harendra Kumar & Shailendra Giri, 2021. "A New Approach for Solving the Flow Shop Scheduling Problem Through Neural Network Technique With Known Breakdown Time and Weights of Jobs," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 12(1), pages 77-96, January.
    • Handle: RePEc:igg:jssmet:v:12:y:2021:i:1:p:77-96
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