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Solving multi objective facility layout problem by modified simulated annealing

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  • Matai, Rajesh

Abstract

This paper proposes a modified simulated annealing approach for solving multi objective facility layout problem. Multi objective facility layout problem is solved by using different objective weights which are generated by decision maker. Thus layout design process is decision maker dependent. However proposed approach in this paper makes layout design process independent of decision maker. Proposed approach can also incorporate any number of objectives that may be qualitative or quantitative in nature. Computational results show superiority of proposed heuristic approach than other approaches available in literature. Finally, comparison was also made with best solution qualities for the 15 single objective test problems of Nugxx series taken from QAPLIB. Comparisons were made in terms of the quality of the solutions obtained and the computational time required and this comparison shows efficiency and effectiveness of proposed modified simulated annealing algorithm.

Suggested Citation

  • Matai, Rajesh, 2015. "Solving multi objective facility layout problem by modified simulated annealing," Applied Mathematics and Computation, Elsevier, vol. 261(C), pages 302-311.
    • Handle: RePEc:eee:apmaco:v:261:y:2015:i:c:p:302-311
    DOI: 10.1016/j.amc.2015.03.107
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    References listed on IDEAS

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    1. Kusiak, Andrew & Heragu, Sunderesh S., 1987. "The facility layout problem," European Journal of Operational Research, Elsevier, vol. 29(3), pages 229-251, June.
    2. Heragu, Sunderesh S., 1992. "Recent models and techniques for solving the layout problem," European Journal of Operational Research, Elsevier, vol. 57(2), pages 136-144, March.
    3. Connolly, David T., 1990. "An improved annealing scheme for the QAP," European Journal of Operational Research, Elsevier, vol. 46(1), pages 93-100, May.
    4. Waghodekar, P. H. & Sahu, Sadananda, 1986. "Facilities layout with multiple objectives: MFLAP," Engineering Costs and Production Economics, Elsevier, vol. 10(2), pages 105-112, June.
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    Cited by:

    1. Rui Li & Yali Chen & Jinzhao Song & Ming Li & Yu Yu, 2023. "Multi-Objective Optimization Method of Industrial Workshop Layout from the Perspective of Low Carbon," Sustainability, MDPI, vol. 15(16), pages 1-23, August.
    2. 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.
    3. Jerzy Grobelny & Rafal Michalski, 2017. "A novel version of simulated annealing based on linguistic patterns for solving facility layout problems," WORking papers in Management Science (WORMS) WORMS/17/07, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    4. Zhongwei Zhang & Lihui Wu & Zhaoyun Wu & Wenqiang Zhang & Shun Jia & Tao Peng, 2022. "Energy-Saving Oriented Manufacturing Workshop Facility Layout: A Solution Approach Using Multi-Objective Particle Swarm Optimization," Sustainability, MDPI, vol. 14(5), pages 1-28, February.
    5. Vincent F. Yu & Shih-Wei Lin & Panca Jodiawan & Yu-Chi Lai, 2023. "Solving the Flying Sidekick Traveling Salesman Problem by a Simulated Annealing Heuristic," Mathematics, MDPI, vol. 11(20), pages 1-21, October.
    6. Parveen Sharma & Sandeep Singhal, 2016. "Design and evaluation of layout alternatives to enhance the performance of industry," OPSEARCH, Springer;Operational Research Society of India, vol. 53(4), pages 741-760, December.
    7. Simge Yelkenci Kose & Ozcan Kilincci, 2020. "A multi-objective hybrid evolutionary approach for buffer allocation in open serial production lines," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 33-51, January.
    8. Irawan, Chandra Ade & Song, Xiang & Jones, Dylan & Akbari, Negar, 2017. "Layout optimisation for an installation port of an offshore wind farm," European Journal of Operational Research, Elsevier, vol. 259(1), pages 67-83.

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