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An application of Genetic algorithms with Constraint-based facility layout problem

Researcher

เครือข่ายคณะผู้วิจัย


เครือข่ายนักวิจัย+ผลงานวิจัย (full screen)

Abstract

Constraint-based facility layout problem (CBFLP) is an important problem for industrial engineer not only for setting up the new facility layouts but also improving the currently used facility layouts. Those constraints, limitations of department arrangement in facility layout, emerge from users or operators requirement which response to maximize their usage or satisfaction. The constraints of facility layout from users in this research can be classified to many ways such as users can specify shape of total area to nonrectangular area, users can fix position of some department in any total area, users can define shape of some department for install specific shape machine or department, users can specify minimum area of some department, users can determine minimum Aspect ratio of department. Moreover, material flow in such facility layout is time independent generally; it is not a constant number especially in non-automatic plant. Thus, fuzzy interflow can be an estimation of material flow efficiently. By defining the flow volumes between departments i.e. best case, near-best case, near-worst case, and worse case; they can be replaced by trapezoidal fuzzy number (TrFN) hence they can be used to estimate the flow volume between departments. This kind of mentioned problem known as NP-Complete problem and classified in the class of combinatorial optimization, and the material flow has to be formalized by using fuzzy set. This research proposes Multi Objective Fuzzy-Genetic algorithms (MOFGA) for arranging departments in facility layout with mentioned constraints, Objective functions and fuzzy material flow. The objectives are to minimize cost of material flow, aisle relationship and total closeness rating, and to arrange departments or machines by restricted constraints of user. Through Performance comparisons, it is found that MOFGA performs equally well or significantly better than the MCRAFT heuristic. In addition, MOFGA is a promising solution technique in searching for a good solution with an acceptable time limit.

Constraint-based facility layout problem (1 items found) | Performance comparison (65 items found) | Objective functions (132 items found) | Genetic algorithms (740 items found) | Aspect ratio (143 items found) | Multi objective fuzzy-genetic algorithmsConstraint-based | Trapezoidal fuzzy numbers | Computational complexity | Facility layout problems | Fuzzy genetic algorithms | Industrial engineering | Solution techniques | Time independents | Plant layout | Fuzzy sets | Materials |

ต้นฉบับข้อมูล : scopus