Rotated test problems for assessing the performance of multiobjective optimization algorithms

Iorio, A and Li, X 2006, 'Rotated test problems for assessing the performance of multiobjective optimization algorithms', in M. Keijzer et al. (ed.) Proceedings of Genetic and Evolutionary Computation Conference 2006 (GECCO 2006), Seattle, USA, 2006, pp. 683-690.


Document type: Conference Paper
Collection: Conference Papers

Title Rotated test problems for assessing the performance of multiobjective optimization algorithms
Author(s) Iorio, A
Li, X
Year 2006
Conference name Genetic and Evolutionary Computation Conference
Conference location Seattle, USA
Conference dates 2006
Proceedings title Proceedings of Genetic and Evolutionary Computation Conference 2006 (GECCO 2006)
Editor(s) M. Keijzer et al.
Publisher ACM Press
Place of publication New York, USA
Start page 683
End page 690
Total pages 8
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).
Subjects Analysis of Algorithms and Complexity
Keyword(s) evolutionary computing
Copyright notice © 2006 ACM
ISBN 1-59593-186-4
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