A simulated annealing algorithm for dynamic layout problem |
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Authors: | Adil Nabil N. Z. |
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Affiliation: | 1. Instituto Federal Fluminense – IFF, Av. Souza Mota, 350, Pq. Fundão, 28060-010 Campos dos Goytacazes, RJ, Brazil;2. Departamento de Engenharia de Produção – Universidade Federal Fluminense, Rua Passo da Pátria 156, São Domingos 24210-240 Niterói, RJ, Brazil;3. Departamento de Informática – PUC–Rio, Rua Marquês de São Vicente, 225, Gávea 22451-900 Rio de Janeiro, RJ, Brazil;1. Industrial Engineering Department, Baskent University, School of Engineering, Eskişehir Yolu 20 km., Bağlica Kampüsü Etimesgut, Ankara 068100, Turkey;2. Department of Industrial and Systems Engineering, University at Buffalo, 309 Bell Hall, Buffalo, NY, USA, 14260-2050;3. Distinguished Professor, Department of Industrial & Systems Engineering, Auburn University, 3301 Shelby Center, Auburn, AL, USA, 36849-5346 |
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Abstract: | Increased level of volatility in today's manufacturing world demanded new approaches for modelling and solving many of its well-known problems like the facility layout problem. Over a decade ago Rosenblatt published a key paper on modelling and solving dynamic version of the facility layout problems. Since then, various other researchers proposed new and improved models and algorithms to solve the problem. Balakrishnan and Cheng have recently published a comprehensive review of the literature about this subject. The problem was defined as a complex combinatorial optimisation problem. The efficiency of SA in solving combinatorial optimisation problems is very well known. However, it has recently not been applied to DLP based on the review of the available literature. In this research paper a SA-based procedure for DLP is developed and results for test problems are reported.Scope and purposeOne of the characteristic of today's manufacturing environments is volatility. Under a volatile environment (or dynamic manufacturing environment) demand is not stable. To operate efficiently under such environments facilities must be adaptive to changing demand conditions. This requires solution of the dynamic layout problem (DLP). DLP is a complex combinatorial optimisation problem for which optimal solutions can be found for small size problems. This research paper makes use of a SA algorithm to solve the DLP. Simulated annealing (SA) is a well-established stochastic neighbourhood search technique. It has a potential to solve complex combinatorial optimisation problems. The paper presents in detail how to apply SA to solve DLP and an extensive computational study. The computational study shows that SA is quite effective in solving dynamic layout problems. |
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Keywords: | Simulated annealing Dynamic layout Optimization |
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