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Solving manufacturing cell design problems using an artificial fish swarm algorithm
dc.contributor.author | Soto R. | |
dc.contributor.author | Crawford B. | |
dc.contributor.author | Vega E. | |
dc.contributor.author | Paredes F. | |
dc.date.accessioned | 2020-09-02T22:28:45Z | |
dc.date.available | 2020-09-02T22:28:45Z | |
dc.date.issued | 2015 | |
dc.identifier | 10.1007/978-3-319-27060-9_23 | |
dc.identifier.citation | 9413, , 282-290 | |
dc.identifier.issn | 03029743 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12728/6333 | |
dc.description | The design of manufacturing cells is a manufacturing strategy that involves the creation of an optimal design of production plants, whose main objective is to minimize movements and exchange of material between these cells. Optimal solution of large scale manufacturing cell design problems (MCDPs) are often computationally unfeasible and only heuristic and approximate methods are able to handle such problems. Artificial fish swarm algorithm (AFSA) belongs to the swarm intelligence algorithms, which based on population search, are able to solve complex optimization problems. In this paper we present an AFSA-based approach to solve the MCDP by using the classic Boctor’s mathematical model. The obtained results show that the proposed algorithm produces optimal solutions for all the 50 studied instances. © Springer International Publishing Switzerland 2015. | |
dc.language.iso | en | |
dc.publisher | Springer Verlag | |
dc.source | Sidorov G.Galicia-Haro S.N. | |
dc.subject | Artificial fish swarm algorithm | |
dc.subject | Manufacturing cell design problem | |
dc.subject | Metaheuristic | |
dc.subject | Algorithms | |
dc.subject | Artificial intelligence | |
dc.subject | Cells | |
dc.subject | Cellular manufacturing | |
dc.subject | Cytology | |
dc.subject | Design | |
dc.subject | Flexible manufacturing systems | |
dc.subject | Heuristic methods | |
dc.subject | Manufacture | |
dc.subject | Optimal systems | |
dc.subject | Optimization | |
dc.subject | Soft computing | |
dc.subject | Approximate methods | |
dc.subject | Artificial fish swarm algorithms | |
dc.subject | Cell design | |
dc.subject | Complex optimization problems | |
dc.subject | Large-scale manufacturing | |
dc.subject | Manufacturing strategy | |
dc.subject | Metaheuristic | |
dc.subject | Swarm intelligence algorithms | |
dc.subject | Problem solving | |
dc.title | Solving manufacturing cell design problems using an artificial fish swarm algorithm | |
dc.type | Conference Paper |