2007 Fiscal Year Final Research Report Summary
Study of Evolutionary Algorithms for Solving Facility Layout Problems
| Project/Area Number |
18510129
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | Hirosaki University (2007)
Tokyo Metropolitan University (2006) |
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Principal Investigator |
SUZUKI Atsushi Hirosaki University, Hirosaki University, Faculty of Humanities, Associate Professor (30249742)
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| Co-Investigator(Kenkyū-buntansha) |
YAMAMOTO Hisashi Tokyo Metropolitan University, Graduate School of System Design, Associate Professor (60231677)
KAINUMA Yasutaka Tokyo Metropolitan University, Faculty of System Design, Associate Professor (90204312)
TSUJIMURA Yasuhiro Nippon Institute of Technology, Faculty of Engineering, Associate Professor (80240977)
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| Project Period (FY) |
2006 – 2007
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| Keywords | facility layout / algorithm |
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| Research Abstract |
In many plants or factories, the location of facilities and the configuration between facilities are related to the effectiveness of material handling and other operational issues. In this study, the problem of deciding spatial location of facilities is called as facility layout problem. In this research project, we focused on operational and other requirements as well as material handling, and considered adjacency preference between facilities. By using adjacency preference, preferable configuration of facilities can be considered minutely. However the problem is complicated because the satisfaction of adjacency preference items is represented to 0 or 1 discrete value of binary variables. We classified layout problems into some types with the problem size. In the case of the number of facilities less than or equal to 14, the problem is regarded as the small size problem, and we developed a new algorithm based on branch and bound method for solving such problems. In the case of the num
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ber is greater than 14, the problem is regarded as large size one, we developed evolutionary algorithms based on simulated annealing technique, genetic algorithms and tabu search method. We compared those algorithms by experiments using numerical examples, and got information of effectiveness of searching and data structure of problems. Moreover, far solving very large scale problem of single floor facility layout; a new algorithm combined simulated annealing and the original neighborhood search method is developed. By using our algorithm on recent personal computers, for large size problem that it is not possible to find the optimum or semi-optimum in practical computation time, it became to be able to find the optimum or the excellent solution. For solving multi floor facility layout problems, we proposed an algorithm based on branch and bound method in the case of small problem, and considering of symmetry layout and other algorithm based on simulated annealing technique to solve large problems. Less
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Research Products
(12 results)
