4.5 Article

Multi-objective facility layout problems using BBO, NSBBO and NSGA-II metaheuristic algorithms

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GROWING SCIENCE
DOI: 10.5267/j.ijiec.2018.6.006

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Multi-objective facility layout problems; Weight approach; Pareto optimality approach; Biogeography-based optimization; Non-dominated sorting biogeography-based optimization

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Quantitative and qualitative objectives are both significant to solve any facility layout problem (FLP), which is called as multi-objective FLP. Generally, quantitative factors are considered as material handling cost, time, etc., and qualitative factors are considered as closeness rating, hazardous movement between the facilities, etc. For solving and optimizing two or more objectives, two methods are available. First is weight approach method and second is non-dominated sorting method. In the former method, suitable weights are given to each objective and combined in a single objective function; while in later method, the objectives are defined separately and by making comparison of the solutions on the non-dominance criteria, best Pareto-optimal solutions are obtained. In this paper, equal area multi-objective FLPs which are formulated as quadratic assignment problem (QAP) are considered and optimized using biogeography based optimization (BBO) algorithm and non-dominated sorting BBO (NSBBO) algorithm. BBO is one of the efficient metaheuristic techniques, developed to solve complex optimization problems. Computational results of BBO algorithm using weight approach illustrate its better performance compared to other methods while solving multi-objective FLPs. Furthermore to obtain Pareto optimal solutions, NSBBO algorithm is implemented. (C) 2019 by the authors; licensee Growing Science, Canada

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