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Formulating multi-objective stochastic dynamic facility layout problem for disaster relief

Author

Listed:
  • Akash Tayal

    (Indira Gandhi Delhi Technical University for Women)

  • Surya Prakash Singh

    (Indian Institute of Technology Delhi)

Abstract

Facility layout problem is an NP-hard problem where two basic approaches have commonly been used to optimize layouts i.e. qualitative and quantitative. Qualitative aspect provide layout based on maximizing of closeness rating while quantitative involve minimization of material handling cost. Previous work undertaken by scholars in which they have studied or focussed on optimizing product flow to optimize both objectives either considering constant or varying demand across all period. Here, the facility layout problem is addressed from the point of demand based disaster for disaster relief operations. Therefore, the paper first presents mathematical formulation for multi objective stochastic dynamic facility layout problem (MO-SDFLP) where the product demand is varying over multiple periods for multiple products. Huge demand variations in multiple products across multiple periods may cause disaster as it can impact heavily the supply chain. Hence, the layout problem considered here mainly focus on considering product demand variations to capture disaster for disaster relief operations. MO-SDFLP being NH-hard is solved using simulated annealing (SA) and chaotic simulated annealing (CSA) meta-heuristics. The paper reports results of SA and CSA algorithms using data sets available in literature for facility size N = 12, period T = 5 and Gaussian distribution product demand. In addition, to show the applicability of MO-SDFLP for bigger demand based disaster, SA and CSA is also tested on bigger problem i.e. N = 30 for T = 5. It is observed that CSA performs better than SA.

Suggested Citation

  • Akash Tayal & Surya Prakash Singh, 2019. "Formulating multi-objective stochastic dynamic facility layout problem for disaster relief," Annals of Operations Research, Springer, vol. 283(1), pages 837-863, December.
    • Handle: RePEc:spr:annopr:v:283:y:2019:i:1:d:10.1007_s10479-017-2592-2
    DOI: 10.1007/s10479-017-2592-2
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    References listed on IDEAS

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    1. Klose, Andreas & Drexl, Andreas, 2005. "Facility location models for distribution system design," European Journal of Operational Research, Elsevier, vol. 162(1), pages 4-29, April.
    2. Kouvelis, Panagiotis & Kiran, Ali S., 1991. "Single and multiple period layout models for automated manufacturing systems," European Journal of Operational Research, Elsevier, vol. 52(3), pages 300-314, June.
    3. Akash Tayal & Angappa Gunasekaran & Surya Prakash Singh & Rameshwar Dubey & Thanos Papadopoulos, 2017. "Formulating and solving sustainable stochastic dynamic facility layout problem: a key to sustainable operations," Annals of Operations Research, Springer, vol. 253(1), pages 621-655, June.
    4. ReVelle, C. S. & Eiselt, H. A., 2005. "Location analysis: A synthesis and survey," European Journal of Operational Research, Elsevier, vol. 165(1), pages 1-19, August.
    5. Balakrishnan, Jaydeep & Jacobs, F. Robert & Venkataramanan, Munirpallam A., 1992. "Solutions for the constrained dynamic facility layout problem," European Journal of Operational Research, Elsevier, vol. 57(2), pages 280-286, March.
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    Cited by:

    1. Adem Erik & Yusuf Kuvvetli, 2024. "A Novel Approach for Material Handling-Driven Facility Layout," Mathematics, MDPI, vol. 12(16), pages 1-37, August.

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