TY - JOUR
T1 - An effective coding approach for multiobjective integrated resource selection and operation sequences problem
AU - Zhang, Haipeng
AU - Gen, Mitsuo
AU - Seo, Yoonho
N1 - Funding Information:
Acknowledgements This work was partly supported by Wased-a University Grant for Special Research Projects 2004, Japanese International Communication Foundation, and the Ministry of Education, Science and Culture, the Japanese Government: Grant-in-Aid for Scientific Research (No.17510138).
PY - 2006/8
Y1 - 2006/8
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
UR - http://www.scopus.com/inward/record.url?scp=33747676002&partnerID=8YFLogxK
U2 - 10.1007/s10845-005-0012-y
DO - 10.1007/s10845-005-0012-y
M3 - Article
AN - SCOPUS:33747676002
SN - 0956-5515
VL - 17
SP - 385
EP - 397
JO - Journal of Intelligent Manufacturing
JF - Journal of Intelligent Manufacturing
IS - 4
ER -