Computer Science ›› 2014, Vol. 41 ›› Issue (2): 114-118.
Previous Articles Next Articles
HOU Wei,DONG Hong-bin and YIN Gui-sheng
| [1] Deb K,Agrawal S,Pratap A,et al．A fast and elitist multi-objective genetic algorithm:NSGA-II [J]．IEEE Transactions on Evo-lutionary Computation,2002,6(2):182-197 [2] Zhou Ai-min,Qu B Y,Li Hui,et al．Multiobjective evolutionary algorithms:A survey of the state of the art [J]．Swarm and Evolutionary Computation,2011,1(1):32-49 [3] Zhang Q F,Li H．MOEA/D:A multiobjective evolutionary algorithm based on decomposition [J]．IEEE Transactions on Evolutionary Computation,2007,1(6):712-731 [4] 公茂果,焦李成,杨咚咚,等．进化多目标优化算法研究 [J]．软件学报,2009,0(2):271-289 [5] Li H,Zhang Q F．Multiobjective optimization problems withcomplicated pareto sets,MOEA/D and NSGA-II [J]．IEEE Transactions on Evolutionary Computation,2009,3(2):284-302 [6] Tan Yan-yan,Jiao Yong-chang,Li Hong,et al．A modification to MOEA/D-DE for multiobjective optimization problems with complicated Pareto sets [J]．Information Sciences,2012,3(5):14-38 [7] Sindhya K,Miettinen K,Deb K．A hybrid framework for evolutionary multi-objective optimization [J]．IEEE Transactions on Evolutionary Computation,2013,7(4):495-511 [8] Fang K T,Lin D K J,Winker P,et al．Uniform design:theory and application [J]．Technometrics,2000,42(3):237-248 [9] He J,Yao X．A game-theoretic approach for designing mixedmutation strategies [C]∥Proceedings of the International Conference on Natural Computation．Berlin:Springer,2005:279-288 [10] Dong Hong-bin,He Jun,Huang Hou-kuan,et al．Evolutionary programming using a mixed mutation strategy [J]．Information Sciences,2007,177(1):312-327 [11] Gong Mao-guo,Liu Chao,Jiao Li-cheng,et al．Hybrid immune algorithm with Lamarckian local search for multi-objective optimization [J]．Memetic Computing,2010,2(1):47-67 [12] Hansen M P．Use of substitute scalarizing functions to guide alocal search based heuristic:The case of moTSP [J]．Journal of Heuristics,2000,6(3):419-431 [13] Jaszkiewicz A．Genetic local search for multi-objective combinatorial optimization [J]．European Journal of Operational Research,2002,137(1):50-71 [14] Sindhya K,Deb K,Miettinen K．A local search based evolutio-nary multi-objective approach for fast and accurate convergence [C]∥Proceedings of the Parallel Problem Solving from Nature-PPSN X．Berlin:Springer,2008:815-824 [15] Talbi E G,Rahoual M,Mabed M,et al．A hybrid evolutionaryapproach for multicriteria optimization problems:Application to the flow shop [C]∥Proceedings of the Evolutionary Multi-Criterion Optimization．Berlin:Springer,2001:416-428 [16] Sindhya K,Deb K,Miettinen K．Improving convergence of evolutionary multi-objective optimization with local search:A concurrent-hybrid algorithm [J]．Natural Computing,2011,10(4):1407-1430 [17] Miettinen K．Nonlinear Multiobjective Optimization [M]．Boston:Kluwer,1999 [18] Huband S,Hingston P,Barone L,et al．A review of multiobjective test problems and a scalable test problem toolkit [J]．IEEE Transactions on Evolutionary Computation,2006,0(5):477-506 [19] Okabe T,Jin Y C,Olhofer M,et al．On test functions for evolutionary multi-objective optimization [C]∥Proceedings of Parallel Problem Solving From Nature-PPSN VIII．Berlin:Springer,2004:792-802 [20] Deb K,Sinha A,Kukkonen S．Multi-objective test problems,linkages,and evolutionary methodologies [C]∥Proceedings of the 8th annual conference on Genetic and Evolutionary Computation (GECCO’06)．New York:ACM,2006:1141-1148 [21] Li H,Zhang Q F．A multi-objective differential evolution based on decomposition for multi-objective optimization with variable linkages [C]∥Proceedings of Parallel Problem Solving from Nature—PPSN IX．Berlin:Springer,2006:583-592 |
| No related articles found! |
|
||
Home