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Integrated SA-DEA-TOPSIS-based solution approach for multi objective stochastic dynamic facility layout problem

Author

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  • Akash Tayal
  • Surya Prakash Singh

Abstract

Layout design often has a significant impact on the performance of a manufacturing industry. In the real world, a facility layout is subjected to various quantitative and qualitative conditions or criteria such as, total material handling cost, flow distance, closeness factor, maintenance etc. Researchers have devised various algorithmic and procedural methodologies for finding a layout that is applicable for practical scenarios. The paper proposes an integrated methodology of combining algorithmic (meta-heuristic) and procedural (decision-making) techniques to identify a layout that has the highest degree of satisfaction for all the criteria. A computer program was developed for simulated annealing. It was used to generate a set of layouts based on qualitative and quantitative aspect of facility layout problem for multiple time periods and uncertain product demand. DEA was applied to identify a subset of efficient layouts. TOPSIS was used to rank these layouts based on criteria and their weights as per expert's opinion.

Suggested Citation

  • Akash Tayal & Surya Prakash Singh, 2017. "Integrated SA-DEA-TOPSIS-based solution approach for multi objective stochastic dynamic facility layout problem," International Journal of Business and Systems Research, Inderscience Enterprises Ltd, vol. 11(1/2), pages 82-100.
    • Handle: RePEc:ids:ijbsre:v:11:y:2017:i:1/2:p:82-100
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    Cited by:

    1. Vadivel Sengazhani Murugesan & A. H. Sequeira & Deeksha Sanjay Shetty & Sunil Kumar Jauhar, 2020. "Enhancement of mail operational performance of India post facility layout using AHP," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 261-273, April.

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