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个人信息Personal Information
教授
博士生导师
硕士生导师
性别：男
毕业院校：德国多德蒙特大学
学位：博士
所在单位：运营与物流管理研究所
学科：企业管理
办公地点：大连理工大学经济管理学院
联系方式：13904286410（因年龄原因，停止招生）
电子邮箱：xbliu@dlut.edu.cn
Improving the Performance of the Pareto Fitness Genetic Algorithm for Multi-Objective Discrete Optimization
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论文类型：会议论文
发表时间：2008-10-17
收录刊物：EI、CPCI-S、Scopus
卷号：2
页面范围：394-+
摘要：To efficiently solve multi-objective discrete optimization problems, combining evolutionary computation with local search, an improved Pareto fitness genetic algorithm (IPFGA) was proposed. In the IPFGA, some features have been added to the original PFGA. The IPFGA after genetic optimization applies a local search on every solution, and adopts an external set truncation strategy to improve search efficiency of evolutionary algorithms. Additionally, the fitness assignment was modified to get more extensive Pareto optimal solutions. The experimental results show that the IPFGA, compared with the PFGA, can improve search efficiency of optimization and find more approximate Pareto optimal solutions.