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Rotated test problems for assessing the performance of multi-objective optimization algorithms

Published: 08 July 2006 Publication History

Abstract

This paper presents four rotatable multi-objective test problems that are designed for testing EMO (Evolutionary Multi-objective Optimization) algorithms on their ability in dealing with parameter interactions. Such problems can be solved efficiently only through simultaneous improvements to each decision variable. Evaluation of EMO algorithms with respect to this class of problem has relevance to real-world problems, which are seldom separable. However, many EMO test problems do not have this characteristic. The proposed set of test problems in this paper is intended to address this important requirement. The design principles of these test problems and a description of each new test problem are presented. Experimental results on these problems using a Differential Evolution Multi-objective Optimization algorithm are presented and contrasted with the Non-dominated Sorting Genetic Algorithm II (NSGA-II).

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      cover image ACM Conferences
      GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation
      July 2006
      2004 pages
      ISBN:1595931864
      DOI:10.1145/1143997
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      Published: 08 July 2006

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      Author Tags

      1. multi-objective optimization
      2. parameter interactions

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      GECCO06: Genetic and Evolutionary Computation Conference
      July 8 - 12, 2006
      Washington, Seattle, USA

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      GECCO '06 Paper Acceptance Rate 205 of 446 submissions, 46%;
      Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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      • (2012)Cooperatively Coevolving Particle Swarms for Large Scale OptimizationIEEE Transactions on Evolutionary Computation10.1109/TEVC.2011.211266216:2(210-224)Online publication date: 1-Apr-2012
      • (2011)A modified particle swarm optimization for correlated phenomenaApplied Soft Computing10.1016/j.asoc.2011.07.01811:8(4640-4654)Online publication date: 1-Dec-2011
      • (2011)Improving the performance and scalability of Differential Evolution on problems exhibiting parameter interactionsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-010-0614-y15:9(1769-1792)Online publication date: 1-Sep-2011
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      • (2010)Multiobjective OptimizationIntroduction to Evolutionary Algorithms10.1007/978-1-84996-129-5_6(193-262)Online publication date: 2010
      • (2009)Tackling high dimensional nonseparable optimization problems by cooperatively coevolving particle swarmsProceedings of the Eleventh conference on Congress on Evolutionary Computation10.5555/1689599.1689803(1546-1553)Online publication date: 18-May-2009
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