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基于偏好方向的区间多目标交互进化算法

, PP. 542-546

Keywords: 进化算法,交互,多目标优化,区间,偏好方向

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Abstract:

区间多目标优化问题在实际应用中普遍存在且非常重要.为得到贴合决策者偏好的最满意解,采用边优化边决策的方法,提出一种交互进化算法.该算法通过请求决策者从部分非被支配解中选择一个最差解,提取决策者的偏好方向,基于该偏好方向设计反映候选解逼近性能的测度,将具有相同序值和决策者偏好的候选解排序.将所提方法应用于4个区间2目标优化问题,并与利用偏好多面体解决区间多目标优化问题的进化算法(PPIMOEA)和后验法比较,实验结果验证了所提出方法的有效性和高效性.

References

[1]  Zhao Z H, Han X, Jiang C et al.. A nonlinear
[2]  2010, 42(4):559-573.
[3]  Liu S T. Using geometric programming to profit maximization
[4]  Mathematics and Computation, 2009, 209(2): 259-265.
[5]  Majumder L, Rao S S. Interval-based optimization of aircraft
[6]  wings under landing loads[J]. Computers and Structures, 2009,
[7]  87(3-4): 225-235.
[8]  imprecise multi-objective problem function[C]. Proc of IEEE Int
[9]  Evolutionary Computation. NewYork: IEEE Press, 2005: 459-466.
[10]  for multi-objective optimization problems with interval
[11]  NewYork: IEEE Press, 2010: 411-420.
[12]  (Zhou Y, Gong D W, Zhang Y. Evolutionary optimization methods
[13]  for hybrid index optimization problems and application[J]. Control and Decision,
[14]  2007, 22(3): 352-356.)
[15]  genetic algorithms[C]. Proc of First International Conference on
[16]  Genetic Algorithms. New Jersey: Lawrence Erlbaum Press,
[17]  Evolutionary Computation, 2002, 6(2): 182-197.
[18]  Branke J, Deb K, Miettinen K et al..
[19]  Multiobjective Optimization - Interactive and Evolutionary
[20]  Coello C A C. Handling Preferences in Evolutionary Multiobjective
[21]  Optimization: A Survey[C], Proc of IEEE Evolutionary Computation.
[22]  New York: IEEE Press, 2000: 30-37.
[23]  Rachmawati L, Srinivasan D. Preference Incorporation in Multi-objective
[24]  Computation. New York: IEEE Press, 2006: 962-968.
[25]  polyhedron[C]. Proc of Genetic and Evolutionary Computation
[26]  Deb K, Koksalan M. Guest Editorial: Special issue
[27]  on preference-based multiobjective evolutionary algorithms [J]. IEEE
[28]  Transactions on Evolutionary Computation, 2010, 14(5): 669-670.
[29]  Luque M, Miettinen K, Eskelinen P et al.. Incorporating
[30]  preference information in interactive reference point[J]. Omega,
[31]  2009, 37(2): 450-462.
[32]  Deb K, Kumar A. Interactive evolutionary multi-objective
[33]  optimization and decision-making using reference direction
[34]  Rachmawati L, Srinivasan D. Incorporating the notion of relative
[35]  optimization[J]. IEEE Transactions on Evolutionary Computation,
[36]  optimization: A genetic algorithm adapting to the decision maker[J].
[37]  IEEE Transactions on Evolutionary Computation, 2010,14(5): 671-687.
[38]  Fowler J W, Gel E S, Koksalan M M et al..
[39]  quasi-concave preference functions[J]. European Journal of
[40]  Operational Research, 2010, 206(2): 417-425.
[41]  Sinha A, Deb K, Korhonen P et al.. An interactive
[42]  Narula S C, Kirilov L, Vassilev V. Reference direction approach for
[43]  solving multiple objective nonlinear programming problems[J]. IEEE
[44]  Transactions on System, Man, and Cybernetics, 1994, 24(5): 804-806.
[45]  Moore R E, Kearfott R B, Cloud M J.Introduction to Interval
[46]  interval-based optimization method with local-densifying
[47]  approximation technique[J]. Structure Multidisplinary Optimization,
[48]  with interval coefficients and quantity discount[J]. Applied
[49]  Limbourg P, Aponte D E S. An optimizaiton algorithm for
[50]  Gong D W, Qin N N, Sun X Y. Evolutionary optimization algorithm
[51]  parameters[C]. Proc of Fifth
[52]  IEEE Int Bio-Inspired Computing: Theories and Applications.
[53]  周勇,巩敦卫,张勇. 混合性能指标优化问题的进化优化方法及应用[J].控制与决策, 2007, 22(3): 352-356.\\
[54]  Schaffer J D. Multiple objective optimization with vector evaluated
[55]  1985:93-100.
[56]  Deb K, Pratap A, Agarwal S et al.. A fast and elitist
[57]  multiobjective genetic algorithm: NSGA-II[J]. IEEE Transactions on
[58]  Approaches[C]. LNCS volume 5252. Heidelberg: Springer Press,
[59]  2008:1-193.
[60]  Evolutionary Algorithms: A Survey[C], Proc of IEEE Int Evolutionary
[61]  Sun J, Gong D W, Sun X Y. Solving interval multi-objective
[62]  optimization problems using evolutionary algorithms with preference
[63]  Conference. New York: ACM Press, 2011: 729-736.
[64]  method[R].India: Indian Institue of Technology, 2007.
[65]  importance of objectives in evolutionary multiobjective
[66]  2010, 14(4): 530-546.
[67]  Battiti R, Passerini A. Brain-computer evolutionary multiobjective
[68]  Deb K, Sinha A, Korhonen P et al.. An interactive evolutionary
[69]  multi-objective optimization method based on progressively approximated value
[70]  functions[R].India:Indian Institue of Technology, 2009.
[71]  Interactive evolutionary multi-objective optimization for
[72]  evolutionary multi-objective optimization method based on polyhedral
[73]  cones[C]. Proc of Learning and Intelligent Optimization Conference.
[74]  New Jersey: Lawrence Erlbaum Press, 2010: 318-332.
[75]  Analysis[M].Philadelphia: SIAM, 2009:9-10.

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