SMS-EMOA: Multiobjective selection based on dominated hypervolume

被引:1363
作者
Beume, Nicola [1 ]
Naujoks, Boris
Emmerich, Michael
机构
[1] Univ Dortmund, Chair Algorithm Engn, D-44221 Dortmund, Germany
[2] Leiden Univ, Leiden Inst Adv Comp Sci, NL-2333 CA Leiden, Netherlands
关键词
evolutionary computations; evolutionary multiple objective optimisation; performance assessment; hypervolume measure; OR in aerodynamic industries;
D O I
10.1016/j.ejor.2006.08.008
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
The hypervolume measure (or L metric) is a frequently applied quality measure for comparing the results of evolutionary multiobjective optimisation algorithms (EMOA). The new idea is to aim explicitly for the maximisation of the dominated hypervolume within the optimisation process. A steady-state EMOA is proposed that features a selection operator based on the hypervolume measure combined with the concept of non-dominated sorting. The algorithm's population evolves to a well-distributed set of solutions, thereby focussing on interesting regions of the Pareto front. The performance of the devised L metric selection EMOA (SMS-EMOA) is compared to state-of-the-art methods on two- and three-objective benchmark suites as well as on aeronautical real-world applications. (C) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:1653 / 1669
页数:17
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