Over the past few years, researchers have developed a number of multi-objective evolutionary algorithms (MOEAs). Although most studies concentrated on solving unconstrained optimization problems, there exists a few studies where MOEAs have been extended to solve constrained optimization problems. As the constraint handling MOEAs gets popular, there is a need for developing test problems which can evaluate the algorithms well. In this paper, we review a number of test problems used in the literature and then suggest a set of tunable test problems for constraint handling. Finally, NSGA-II with an innovative constraint handling strategy is compared with a couple of existing algorithms in solving some of the test problems. © Springer-Verlag Berlin Heidelberg 2001.
CITATION STYLE
Deb, K., Pratap, A., & Meyarivan, T. (2001). Constrained test problems for multi-objective evolutionary optimization. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1993, 284–298. https://doi.org/10.1007/3-540-44719-9_20
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