Abstract
In this paper, we consider an integrated Resource Selection and Operation Sequences (iRS/OS) problem in Intelligent Manufacturing System (IMS). Several kinds of objectives are taken into account, in which the makespan for orders should be minimized; workloads among machine tools should be balanced; the total transition times between machines in a local plant should also be minimized. To solve this multiobjective iRS/OS model, a new two vectors-based coding approach has been proposed to improve the efficiency by designing a chromosome containing two kinds of information, i.e., operation sequences and machine selection. Using such kind of chromosome, we adapt multistage operation-based Genetic Algorithm (moGA) to find the Pareto optimal solutions. Moreover a special technique called left-shift hillclimber has been used as one kind of local search to improve the efficiency of our algorithm. Finally, the experimental results of several iRS/OS problems indicate that our proposed approach can obtain best solutions. Further more comparing with previous approaches, moGA performs better for finding Pareto solutions.
| Original language | English |
|---|---|
| Pages (from-to) | 385-397 |
| Number of pages | 13 |
| Journal | Journal of Intelligent Manufacturing |
| Volume | 17 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2006 Aug 1 |
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Keywords
- Integrated resource selection and operation sequences
- Intelligent manufacturing system
- Left-shift hillclimber
- Multiple criteria model
- Multistage operation-based genetic algorithm
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Artificial Intelligence
Cite this
An effective coding approach for multiobjective integrated resource selection and operation sequences problem. / Zhang, Haipeng; Gen, Mitsuo; Seo, Yoon Ho.
In: Journal of Intelligent Manufacturing, Vol. 17, No. 4, 01.08.2006, p. 385-397.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An effective coding approach for multiobjective integrated resource selection and operation sequences problem
AU - Zhang, Haipeng
AU - Gen, Mitsuo
AU - Seo, Yoon Ho
PY - 2006/8/1
Y1 - 2006/8/1
N2 - In this paper, we consider an integrated Resource Selection and Operation Sequences (iRS/OS) problem in Intelligent Manufacturing System (IMS). Several kinds of objectives are taken into account, in which the makespan for orders should be minimized; workloads among machine tools should be balanced; the total transition times between machines in a local plant should also be minimized. To solve this multiobjective iRS/OS model, a new two vectors-based coding approach has been proposed to improve the efficiency by designing a chromosome containing two kinds of information, i.e., operation sequences and machine selection. Using such kind of chromosome, we adapt multistage operation-based Genetic Algorithm (moGA) to find the Pareto optimal solutions. Moreover a special technique called left-shift hillclimber has been used as one kind of local search to improve the efficiency of our algorithm. Finally, the experimental results of several iRS/OS problems indicate that our proposed approach can obtain best solutions. Further more comparing with previous approaches, moGA performs better for finding Pareto solutions.
AB - In this paper, we consider an integrated Resource Selection and Operation Sequences (iRS/OS) problem in Intelligent Manufacturing System (IMS). Several kinds of objectives are taken into account, in which the makespan for orders should be minimized; workloads among machine tools should be balanced; the total transition times between machines in a local plant should also be minimized. To solve this multiobjective iRS/OS model, a new two vectors-based coding approach has been proposed to improve the efficiency by designing a chromosome containing two kinds of information, i.e., operation sequences and machine selection. Using such kind of chromosome, we adapt multistage operation-based Genetic Algorithm (moGA) to find the Pareto optimal solutions. Moreover a special technique called left-shift hillclimber has been used as one kind of local search to improve the efficiency of our algorithm. Finally, the experimental results of several iRS/OS problems indicate that our proposed approach can obtain best solutions. Further more comparing with previous approaches, moGA performs better for finding Pareto solutions.
KW - Integrated resource selection and operation sequences
KW - Intelligent manufacturing system
KW - Left-shift hillclimber
KW - Multiple criteria model
KW - Multistage operation-based genetic algorithm
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UR - http://www.scopus.com/inward/citedby.url?scp=33747676002&partnerID=8YFLogxK
U2 - 10.1007/s10845-005-0012-y
DO - 10.1007/s10845-005-0012-y
M3 - Article
AN - SCOPUS:33747676002
VL - 17
SP - 385
EP - 397
JO - Journal of Intelligent Manufacturing
JF - Journal of Intelligent Manufacturing
SN - 0956-5515
IS - 4
ER -