Solving fuzzy robust facility layout problem equipped with cranes using MPS algorithm and modified NSGA-II

•A fuzzy robust facility layout problem is described.•Cranes are considered in the plant region.•Two proposed meta-heuristic algorithms were used to solve the problem. Facility layout problems are defined as the placement of facilities in a plant region. In this paper a facility layout problem was c...

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Veröffentlicht in:Expert systems with applications 2022-12, Vol.210, p.118402, Article 118402
Hauptverfasser: Esmikhani, Soroush, Kazemipoor, Hamed, Sobhani, Farzad Movahedi, Molana, Seyyed Mohammad Hadji
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Sprache:eng
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Zusammenfassung:•A fuzzy robust facility layout problem is described.•Cranes are considered in the plant region.•Two proposed meta-heuristic algorithms were used to solve the problem. Facility layout problems are defined as the placement of facilities in a plant region. In this paper a facility layout problem was clarified by the facility dimensions and the materials flow between facilities are uncertain as fuzzy random variables and the plant region was equipped with the wall mounted jib cranes and the small gate cranes and there were some forbidden areas in the plant region where the placement of facilities were forbidden. The objective functions of the problems have been contemplated as minimizing materials handling cost of the operators and the cranes and for the first time maximizing cranes usability of wall mounted jib cranes and small gate cranes by calculating their covered area on the facilities. To solve the problem a multi-objective population-based on simulated annealing algorithm (MPS) and a Modified Non-dominated Sorting Genetic Algorithm II (MNSGA-II) was proposed then six case studies were solved by them. The results reveal that run time of the MNSGA-II for large size problems are better than the MPS algorithm and the MPS algorithm finds better solutions with materials handling cost of the operators and the cranes and the MNSGA-II finds better solutions with cranes usability.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2022.118402