三峡大学机械与动力学院,湖北,宜昌,443002
纸质出版:2016
移动端阅览
[1]张屹,万兴余,郑小东,孙莉莉.基于正交设计的元胞多目标遗传算法[J].电子学报,2016,44(01):87-94.
ZHANG Yi, WAN Xing-yu, ZHENG Xiao-dong, et al. Cellular Genetic Algorithm for Multiobjective Optimization Based on Orthogonal Design[J]. Acta Electronica Sinica, 2016, 44(1): 87-94.
[1]张屹,万兴余,郑小东,孙莉莉.基于正交设计的元胞多目标遗传算法[J].电子学报,2016,44(01):87-94. DOI: 10.3969/j.issn.0372-2112.2016.01.013.
ZHANG Yi, WAN Xing-yu, ZHENG Xiao-dong, et al. Cellular Genetic Algorithm for Multiobjective Optimization Based on Orthogonal Design[J]. Acta Electronica Sinica, 2016, 44(1): 87-94. DOI: 10.3969/j.issn.0372-2112.2016.01.013.
元胞多目标遗传算法在求解两目标优化问题时是比较高效的.但是
初步实验显示其在求解三目标优化问题(例如DTLZ系列)时
表现不是十分令人满意.为了进一步提高算法的性能
引入了正交设计的思想
提出了基于正交设计的多目标元胞遗传算法.在改进算法的迭代过程中
先对父代个体进行分段
之后按照正交表来对这些片段进行重新组合产生多个子代个体
然后从这些子代个体中找出适应度较优的进入下一代种群.实验结果表明
引入正交设计思想能够提高算法性能
与其他优秀算法进行比较的结果说明
改进算法求解三目标问题(DTLZ系列)也是具有竞争力的.
Multi-objective cellular genetic algorithm has proven to be effective in solving bi-objective MOPs.However
preliminary experiments have revealed that it has difficulties when dealing with three-objective MOPs(the DTLZ problem family).In order to enhance the performance
the orthogonal design idea is introduced and a new cellular genetic algorithm called cellular genetic algorithm for multi-objective optimization based on orthogonal design is proposed.In the progress of iteration of improved algorithm
the parent individuals are divided into many segments
and then several offsprings are produced by recombining the segments according to the orthogonal table
finally
choose the individuals which have better fitness value from the offsprings to the next population.The experiments show that the performance is improved after introducing the orthogonal design.Compared with several state-of-the-art multi-objective metaheuristics
the obtained results show that the improved algorithm is competitive for DTLZ problem family
too.
进化算法的困难性理论研究进展 [J]. 李坤,黎明,陈昊. 电子学报 . 2014(02)
基于集合的高维多目标优化问题的进化算法 [J]. 巩敦卫,季新芳,孙晓燕. 电子学报 . 2014(01)
一种多目标进化算法解集分布广度评价方法 [J]. 李密青,郑金华. 计算机学报 . 2011(04)
Enhancing the search ability of differential evolution through orthogonal crossover [J] . Yong Wang,Zixing Cai,Qingfu Zhang. Information Sciences . 2011 (1)
Enhancing the performance of differential evolution using orthogonal design method [J] . Wenyin Gong,Zhihua Cai,Liangxiao Jiang. Applied Mathematics and Computation . 2008 (1)
An orthogonal design based constrained evolutionary optimization algorithm [J] . Yong Wang,Hui Liu,Zixing Cai,Yuren Zhou. Engineering Optimization . 2007 (6)
A cellular multi-objective genetic algorithm for optimal broadcasting strategy in metropolitan MANETs [J] . E. Alba,B. Dorronsoro,F. Luna,A.J. Nebro,P. Bouvry,L. Hogie. Computer Communications . 2006 (4)
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results [J] . Eckart Zitzler,Kalyanmoy Deb,Lothar Thiele. Evolutionary Computation . 2000 (2)
MEA:A metapopulation evolutionary algorithm for multi-objective optimisation problems . Kirley M. Proceedings of the2001 Congress on Evolutionary Computation . 2001
Balancing exploration and exploitation in an adaptive three-dimensional cellular genetic algorithm via a probabilistic selection operator . Al-Naqi A,Erdogan A T,Arslan T,et al. Proceedings of the Conference on Adaptive Hardware and Systems(AHS) . 2010
A scalable multi-objective testproblem toolkit . Huband S,Barone L,While L, et al. Evolutionary multi-criterion optimization . 2005
Comparison of multiobjective evolutionary algorithms: empirical results . Eckart Zitzler, Kalyanmoy Deb, Lothar Thiele. Evolutionary Computation . 2000
The exploration/exploitation tradeoff in dynamic cellular genetic algorithms . E. Alba,B. Dorronsoro. IEEE Transactions on Evolutionary Computation . 2005
An Evolutionary Algorithm for Global Optimization Based on Level-Set Evolution and Latin Squares . Yuping Wang,Chuangyin Dang. IEEE Transactions on Evolutionary Computation . 2007
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition . Qingfu Zhang,Hui Li. IEEE Transactions on Evolutionary Computation . 2007
Multiobjective genetic programming:Reducing bloat using SPEA2 . Bleuler S,Brack M,Thiele L,et al. Proceedings of the 2001 Congress on Evolutionary Computation . 2001
Parallel Problem Solving from Nature–PPSN X . Durillo J J,Nebro A J,Luna F, et al. . 2008
An orthogonal multi-objective evolutionary algorithm for multi-objective optimization problems with constraints . Zeng Sanyou Y,Kang Lishan S,Ding Lixin X. Evolutionary Computation . 2004
Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach . Zitzler E, Thiele L. IEEE Transactions on Evolutionary Computation . 1999
The influence of grid shape and asynchronicity on cellular evolutionary algorithms . Dorronsoro B,Alba E,Giacobini M,et al. Proceedings of the Congress on Evolutionary Computation . 2004
Multiobjective Evolutionary Algorithm Research: A History and Analysis . Veldhuizen DAV, Lamont GB. Technical Report TR-98-03 . 1998
Scalable Multi-Objective Optimization Test Problems . Deb K, Thiele L, Laumanns M, et al. Proceedings of the 2002 Congress on Evolutionary Computation . 2002
An orthogonal genetic algorithm for multimedia multicast routing . Zhang Qingfu, Leung Yiuwing. IEEE Transactions on Evolutionary Computation . 1999
The pareto archived evolution strategy: A new baseline algorithm for multi-objective optimization . Knowles JD, Corne DW. Proceedings of the 1999 Congress on Evolutionary Computation (CEC’99) . 1999
An orthogonal genetic algorithm with quantization for global numerical optimization . Leung Yiu-Wing, Wang Yu-ping. IEEE Transactions on Evolutionary Computation . 2001
MOCell: A cellular genetic algorithm for multiobjective optimization . Nebro, Antonio J,Durillo, Juan J,Luna, Francisco,Dorronsoro, Bernabé,Alba, Enrique. International Journal of Intelligent Systems . 2009
A fast and elitist multiobjective genetic algorithm: NSGA-II . K. Deb,A. Pratap,S. Agarwal, et al. IEEE Transactions on Evolutionary Computation . 2002
0
浏览量
1145
下载量
5
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621