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Solving A Kind of High Complexity Multi-Objective Problems by A Fast Algorithm

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【Author】 Zeng San-you, Ding Li-xin, Kang Li-shanDepartment of Computer Science,China University of GeoSciences, Wuhan 430074, Hubei, China;Department of Computer Science, Zhuzhou Institute of Technology , Zhuzhou 412008, Hunan, China;State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei, China

【摘要】 <正> A fast algorithm is proposed to solve a kind of high complexity multi-objective problems in this paper. It takes advantages of both the orthogonal design method to search evenly, and the statistical optimal method to speed up the computation. It is very suitable for solving high complexity problems, and quickly yields solutions which converge to the Pareto-optimal set with high precision and uniform distribution. Some complicated multi-objective problems are solved by the algorithm and the results show that the algorithm is not only fast but also superior to other MOGAS and MOEAs, such as the currently efficient algorithm SPEA, in terms of the precision, quantity and distribution of solutions.

【Abstract】 A fast algorithm is proposed to solve a kind of high complexity multi-objective problems in this paper. It takes advantages of both the orthogonal design method to search evenly, and the statistical optimal method to speed up the computation. It is very suitable for solving high complexity problems, and quickly yields solutions which converge to the Pareto-optimal set with high precision and uniform distribution. Some complicated multi-objective problems are solved by the algorithm and the results show that the algorithm is not only fast but also superior to other MOGAS and MOEAs, such as the currently efficient algorithm SPEA, in terms of the precision, quantity and distribution of solutions.

【基金】 Supported by the National Natural Science Foundation of China(60204001,70071042,60073043,60133010)and Youth Chengguang Project of Science and Technology of Wuhan City(20025001002)
  • 【文献出处】 Wuhan University Journal of Natural Sciences ,武汉大学学报(自然科学版.英文版) , 编辑部邮箱 ,2003年S1期
  • 【分类号】O224
  • 【被引频次】1
  • 【下载频次】10
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