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Yiangkamolsing, Chana (2005) An Application of Genetic Algorithms With Constant-based Facility Layout Problem. UTCC Engineering Research Papers. ISSN 1906-1625

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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 non-rectangular 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. These constraints are related only with physical arrangement. The solving approach for these constraints is more complicated. In practically, the plant designer must consider any other information together with above constraints. The information can be classified to 3 objective functions. Firstly, the objective function is to minimize cost of material flow. Cost of material flow in such plant layout depend on frequency of flow from department i to department j, unit cost of flow from department i to department j and distance from department i to department j. Secondly, the objective function is to minimize aisle relationship. Aisle relationship of facility layout indicates to the utilization of intersection served area so that it should be minimize. Thirdly, for qualitative data, the objective is to minimize total closeness desirability by moving as closely as possible the departments with high preference of reducing distance between departments. Moreover, material flow in such facility layout is time independent generally; it is not a constant number especially in non-automatic plant. Fuzzy interflow can be an estimation of material flow efficiently. By defining the flow volume i.e. best case, near-best case, near-worst case, and worse case, it can be replaced by trapezoidal fuzzy number (TrFN). 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. Because the performance of MOFGA depends on several parameters; pilot runs and experimental designs have been used to test these parameters including population size, probability of crossover, probability of mutation, selection type, crossover type, and mutation type with many cases of problems for instance small number of department, medium number of department and large number of department. 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.

Item Type: Article
Subjects: Engineering > Industrial Engineering
Divisions: School > School of Engineering
Depositing User: Kitikun Pongsak
Date Deposited: 16 May 2014 20:51
Last Modified: 16 May 2014 20:51
URI: http://eprints.utcc.ac.th/id/eprint/717

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