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

  • Applications of OR in Disaster Relief Operations
  • Published:
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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.

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References

  • Balakrishnan, J., Jacobs, F. R., & Venkataramanan, M. A. (1992). Solution for the constrained dynamic facility layout problem. European Journal of Operation Research, 57, 280–286.

    Article  Google Scholar 

  • Braglia, M., Zanoni, S., & Zavanella, L. (2003). Layout design in dynamic environments: Strategies and quantitative indices. International Journal of Production Research, 41(5), 995–1016.

    Article  Google Scholar 

  • Braglia, M., Zanoni, S., & Zavanella, L. (2005). Layout design in dynamic environments: Analytical issues. International Transition in Operation Research, 12(2005), 1–19.

    Google Scholar 

  • Chen, C. W., & Sha, D. Y. (2001). A literature review and analysis to the facility layout problem. Journal of the Chinese Institute of Industrial Engineers, 18(1), 55–73.

    Article  Google Scholar 

  • Dutta, K. N., & Sahu, S. (1982). A multigoal heuristic for facilities design problem: Mughal. International Journal of Production Research, 20, 147–154.

    Article  Google Scholar 

  • Fortenberry, J. C., & Cox, J. F. (1985). Multiple criteria approach to the facilities layout problem. International Journal of Production Research, 23, 773–782.

    Article  Google Scholar 

  • Haghani, A. (1996). Capacitated maximum covering location models: Formulations and solution procedure. Journal of Advanced Transportation, 30(3), 101–136.

    Article  Google Scholar 

  • Hong, J. D., Jeong, K. Y., & Feng, K. (2015). Emergency relief supply chain design and trade-off analysis. Journal of Humanitarian Logistics and Supply Chain Management, 5(2), 162–187.

    Article  Google Scholar 

  • Kaur, H., & Singh, S. P. (2016). Sustainable procurement and logistics for disaster resilient supply chain. Annals of Operations Research. doi:10.1007/s10479-016-2374-2.

  • Kaur, H., & Singh, S. P. (2017). Flexible dynamic sustainable procurement model. Annals of Operations Research. doi:10.1007/s10479-017-2434-2.

    Article  Google Scholar 

  • Khare, V. K., Khare, M. K., & Neema, M. L. (1988a). Estimation of distribution parameters associated with facilities design problem involving forward and backtracking of materials. Computers Industrial Engineering, 14, 63–75.

    Article  Google Scholar 

  • Khare, V. K., Khare, M. K., & Neema, M. L. (1988b). Combined computer-aided approach for the facilies design problem and estimation of the distribution parameter in the case of multigoal optimization. Computers Industrial Engineering, 14, 465–476.

    Article  Google Scholar 

  • Kirkpatrick, S., Gelatt, C. D, Jr., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220, 671–7.

    Article  Google Scholar 

  • Klose, A., & Drexl, A. (2005). Facility location models for distribution system design. European Journal of Operational Research, 162(1), 4–29.

    Article  Google Scholar 

  • Koopmans, T. C. S., & Beckman, M. (1957). Assignment problem and the location of economic activities. Econometric, 25, 53–76.

    Article  Google Scholar 

  • Kouvelis, P., & Kiran, A. S. (1991). Single and multiple period layout models for automated manufacturing systems. European Journal of Operational Research, 52(3), 300–314.

    Article  Google Scholar 

  • Kulturel-Konak, S. (2007). Approaches to uncertainties in facility layout problem: Perspectives at the beginning of the 21st century. Journal of Intelligent Manufacturing, 14(2), 219–228.

    Article  Google Scholar 

  • Kulturel-Konak, S., Smith, A. E., & Norman, B. A. (2004). Layout optimization considering production uncertainty and routing flexibility. International Journal of Production Research, 42(21), 4475–4493.

  • Matai, R., Singh, S. P., & Mittal, M. L. (2013a). A non-Greedy systematic neighbourhood search heuristic for solving facility layout problem. The International Journal of Advanced Manufacturing Technology, 68, 1665–1675.

    Article  Google Scholar 

  • Matai, R., Singh, S. P., & Mittal, M. L. (2013b). Modified simulated annealing based approach for multi objective facility layout problem. International Journal of Production Research, 51(14), 4273–4288.

    Article  Google Scholar 

  • Matai, R., Singh, S. P., & Mittal, M. L. (2013c). A new heuristic for solving facility layout problem. International Journal of Advanced Operations Management, 5(2), 137–158.

    Article  Google Scholar 

  • Moslemipour, G., & Lee, T. S. (2011). Intelligent design of a dynamic machine layout in uncertain environment of flexible manufacturing systems. Journal of Intelligent Manufacturing, 23(5), 1849–1860.

    Article  Google Scholar 

  • Marianov, V., & ReVelle, C. (1995). Siting emergency services. Facility Location: A Survey of Applications and Methods, 1, 199–223.

    Article  Google Scholar 

  • Mingjun, J., & Huanwen, T. (2004). Application of chaos in simulated annealing. Chaos, Solitons & Fractals, 21(4), 933–941.

    Article  Google Scholar 

  • Papadopoulos, T., Gunasekaran, A., Dubey, R., Childe, S. J., Altay, N., & Wamba, S. F. (2017). The role of Big Data in explaining disaster resilience in supply chains for sustainability. Journal of Cleaner Production, 142(2), 1108–1118.

    Article  Google Scholar 

  • ReVelle, C. S., & Eiselt, H. A. (2005). Location analysis: A synthesis and survey. European Journal of Operational Research, 165(1), 1–19.

    Article  Google Scholar 

  • Rosenblatt, M. J. (1979). The facilities layout problem: A multigoal approach. International Journal of Production Research, 17, 323–332.

    Article  Google Scholar 

  • Rosenblatt, M. J., & Kropp, D. H. (1992). The single period stochastic plan layout problem. IIE Transactions, 24(2), 169–176.

    Article  Google Scholar 

  • Rosenblatt, M. J., & Lee, H. L. (1987). A robustness approach to facilities design. International journal of production research, 25(4), 479–486.

    Article  Google Scholar 

  • Singh, S. P. (2009). Solving facility layout problem: Three-level Tabu search meta-heuristic approach. International Journal of Recent Trends in Engineering, 1(1), 73–77.

    Google Scholar 

  • Singh, S. P., & Sharma, R. R. K. (2006). A review of different approaches to the facility layout problem. The International Journal of Advanced Manufacturing Technology, 30(5–6), 425–433.

    Article  Google Scholar 

  • Singh, S. P., & Sharma, R. R. K. (2008). Two level simulated annealing based approach to solve facility layout problem. International Journal of Production Research, 46(13), 3563–3582.

    Article  Google Scholar 

  • Singh, S. P., & Singh, V. K. (2010). An improved heuristic approach for multi-objective facility layout problem. The International Journal of Production Research, 48(4), 1171–1194.

    Article  Google Scholar 

  • Singh, S. P., & Singh, V. K. (2011). Three-level AHP based heuristic approach to solve multi-objective facility layout problem. International Journal of Production Research, 49(4), 1105–1125.

    Article  Google Scholar 

  • Singh, S. P., Matai, R., & Mittal, M. L. (2012). Solving multi-objective facility layout problem: Modified simulated annealing based approach. European Journal of Management, 12(2), 111–116.

    Google Scholar 

  • Shore, R. H., & Tompkins, J. A. (1980). Flexible facilities design. AIIE Transactions, 12(2), 200–205.

    Google Scholar 

  • Tayal, A., & Singh, S. P. (2014). Chaotic simulated annealing for solving stochastic dynamic facility layout problem. Journal of International Management Studies, 14(2), 67–74.

    Article  Google Scholar 

  • Tayal, A., & Singh, S. P. (2016). Integrating big data analytic and hybrid firefly-chaotic simulated annealing approach for facility layout problem. Annals of Operations Research. doi:10.1007/s10479-016-2237-x.

    Article  Google Scholar 

  • Tayal, A., Gunasekaran, A., Singh, S. P., Dubey, R., & Papadopoulos, T. (2017). Formulating and solving sustainable stochastic dynamic facility layout problem: A key to sustainable operations. Annals of Operations Research, 253, 621–655. doi:10.1007/s10479-016-2351-9.

    Article  Google Scholar 

  • Tompkins, J. A., White, J. A., & Tanchoco, J. M. A. (2003). Facilities planning. New York: Willey.

    Google Scholar 

  • Urban, T. L. (1989). Combining qualitative and quantitative analysis in facility layout. Production and Inventory Management, 30, 73–77.

    Google Scholar 

  • Wang, L., & Smith, K. (1998). On chaotic simulated annealing. IEEE Transactions on Neural Networks, 9, 716–718.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Indira Gandhi Delhi Technical University for Women, New Delhi, India

    Akash Tayal

  2. Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, 110016, India

    Surya Prakash Singh

Authors
  1. Akash Tayal
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  2. Surya Prakash Singh
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Corresponding author

Correspondence to Surya Prakash Singh.

Appendices

Appendix I Adjacency matrix for machines N=12

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Appendix II Adjacency matrix for machines N=30

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Tayal, A., Singh, S.P. Formulating multi-objective stochastic dynamic facility layout problem for disaster relief. Ann Oper Res 283, 837–863 (2019). https://doi.org/10.1007/s10479-017-2592-2

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