Abstract
Most of the algorithms for the facility layout problem (FLP) attempt to solve the problem through encoding layout candidates and using combinational optimization techniques to obtain the best encoded candidates. However, since FLP is a continuous optimization problem by nature, layouts exist which cannot be represented by these encoding techniques. Therefore, there is possibility that the opportunity to search for the optimal solution will be missed. Furthermore, some algorithms attempt to solve FLP as a continuous problem; however, since FLP is a non-convex problem, it is known that these algorithms have the problem of being trapped into local optima. To overcome these problems, this paper proposes an algorithm to solve FLP through applying a real coded genetic algorithm (RCGA), which is known to be effective for many types of continuous optimization problems.
| Original language | English |
|---|---|
| Pages (from-to) | 182-189 |
| Number of pages | 8 |
| Journal | Journal of Japan Industrial Management Association |
| Volume | 62 |
| Issue number | 4 |
| Publication status | Published - 2011 Oct 15 |
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Keywords
- Facility layout problem
- Facility planning
- Material handling
- Optimization
- Real coded genetic algorithm
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Applied Mathematics
- Management Science and Operations Research
- Strategy and Management
Cite this
An optimization method for the facility layout problem using a real-coded genetic algorithm. / Ohmori, Shunichi; Mlyoshl, Kanako; Yoshimoto, Kazuho.
In: Journal of Japan Industrial Management Association, Vol. 62, No. 4, 15.10.2011, p. 182-189.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An optimization method for the facility layout problem using a real-coded genetic algorithm
AU - Ohmori, Shunichi
AU - Mlyoshl, Kanako
AU - Yoshimoto, Kazuho
PY - 2011/10/15
Y1 - 2011/10/15
N2 - Most of the algorithms for the facility layout problem (FLP) attempt to solve the problem through encoding layout candidates and using combinational optimization techniques to obtain the best encoded candidates. However, since FLP is a continuous optimization problem by nature, layouts exist which cannot be represented by these encoding techniques. Therefore, there is possibility that the opportunity to search for the optimal solution will be missed. Furthermore, some algorithms attempt to solve FLP as a continuous problem; however, since FLP is a non-convex problem, it is known that these algorithms have the problem of being trapped into local optima. To overcome these problems, this paper proposes an algorithm to solve FLP through applying a real coded genetic algorithm (RCGA), which is known to be effective for many types of continuous optimization problems.
AB - Most of the algorithms for the facility layout problem (FLP) attempt to solve the problem through encoding layout candidates and using combinational optimization techniques to obtain the best encoded candidates. However, since FLP is a continuous optimization problem by nature, layouts exist which cannot be represented by these encoding techniques. Therefore, there is possibility that the opportunity to search for the optimal solution will be missed. Furthermore, some algorithms attempt to solve FLP as a continuous problem; however, since FLP is a non-convex problem, it is known that these algorithms have the problem of being trapped into local optima. To overcome these problems, this paper proposes an algorithm to solve FLP through applying a real coded genetic algorithm (RCGA), which is known to be effective for many types of continuous optimization problems.
KW - Facility layout problem
KW - Facility planning
KW - Material handling
KW - Optimization
KW - Real coded genetic algorithm
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UR - http://www.scopus.com/inward/citedby.url?scp=84857264208&partnerID=8YFLogxK
M3 - Article
VL - 62
SP - 182
EP - 189
JO - Journal of Japan Industrial Management Association
JF - Journal of Japan Industrial Management Association
SN - 0386-4812
IS - 4
ER -