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 |
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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 |
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
- Software
- Industrial and Manufacturing Engineering
- Artificial Intelligence