دورية
The Improved Genetic Algorithm for Multi-Objective Flexible Job Shop Scheduling Problem
| العنوان: | The Improved Genetic Algorithm for Multi-Objective Flexible Job Shop Scheduling Problem |
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| المؤلفون: | Yang, Jian Jun, Ju, Lu Yan, Liu, Bao Ye |
| المصدر: | Applied Mechanics and Materials; July 2011, Vol. 66 Issue: 1 p870-875, 6p |
| مستخلص: | To solve the multi-objective flexible job shop scheduling problem, an improved non-dominated sorting genetic algorithm is proposed. Multi-objective mathematical model is established, four objectives, makespan, maximal workload, total workload and total tardiness are considered together. In this paper a dual coding method is employed, and infeasible solutions were avoided by new crossover and mutation methods. Pareto optimal set was taken to deal with multi-objective optimization problem, in order to reduce computational complexity, the non-dominated sorting method was improved. The niche technology is adopted to increase the diversity of solutions, and a new self adaptive mutation rate computing method is designed. The proposed algorithm is tested on some instances, and the computation results demonstrate the superiority of the algorithm. |
| قاعدة البيانات: | Supplemental Index |
Full Text Finder | تدمد: | 16609336 16627482 |
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| DOI: | 10.4028/www.scientific.net/AMM.66-68.870 |