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机构地区:[1]Department of Production Engineering, Jadavpur University, Kolkata, India
出 处:《Intelligent Information Management》2012年第6期319-329,共11页智能信息管理(英文)
摘 要:This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contains a new mutation algorithm and has been applied on a bi-objective job sequencing problem. The objectives are the minimization of total weighted tardiness and the minimization of the deterioration cost. The results of the proposed algorithm have been compared with those of original NSGA-II. The comparison of the results shows that the modified NSGA-II performs better than the original NSGA-II.This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contains a new mutation algorithm and has been applied on a bi-objective job sequencing problem. The objectives are the minimization of total weighted tardiness and the minimization of the deterioration cost. The results of the proposed algorithm have been compared with those of original NSGA-II. The comparison of the results shows that the modified NSGA-II performs better than the original NSGA-II.
关 键 词:JOB SEQUENCING Multi-Objective Evolutionary Algorithm (MOEA) NSGA-II (Non-Dominated Sorting Genetic Algorithm-II) TARDINESS DETERIORATION Cost
分 类 号:TP1[自动化与计算机技术—控制理论与控制工程]
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