NDLI: A Dynamic Multi-Objective Evolutionary Algorithm Based on an Orthogonal Design

Content Provider	IEEE Xplore Digital Library
Author	Sang-you Zeng Guang Chen Liang Zheng Hui Shi de Garis, H. Lixin Ding Lishan Kang
Copyright Year	2006
Description	Author affiliation: China Univ. of Geosci., Wuhan (Sang-you Zeng; Guang Chen; Liang Zheng; Hui Shi; de Garis, H.)
Abstract	There are rather few articles in the literature so far that deal with dynamic multi-objective optimization problems. This article introduces a dynamic orthogonal multi-objective evolutionary algorithm called "DOMOEA", that generalizes an earlier paper of ours (on an orthogonal multi-objective evolutionary algorithm (OMOEA-II) (Zeng et al., 2005)) to dynamic environments. DOMOEA solves a particular class of dynamic multi-objective optimization problems, namely those that have continuous decision variables. This new algorithm uses the evolutionary results, before any environmental change, as the initial population after the environmental change. It applies an "orthogonal design method" to enhance the fitness of the population during the static stages between two successive changes of environment. We obtained satisfactory results when testing this algorithm against the benchmark problems proposed in the literature. Our new algorithm is based on an ordinary evolutionary algorithm that does not have the capacity to detect environmental changes. Hence it has a comparatively simple structure, making comparisons with other dynamic multi-objective evolutionary algorithms relatively easy.
Starting Page	573
Ending Page	580
File Size	457734
Page Count	8
File Format	PDF
ISBN	0780394879
DOI	10.1109/CEC.2006.1688361
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-16
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Evolutionary computation Algorithm design and analysis Design optimization Space technology Design methodology Heuristic algorithms Change detection algorithms Constraint optimization Computer science Convergence Pareto optimal front (POF) Evolutionary algorithm orthogonal design dynamic multi-objective optimization Pareto optimal set (POS)
Content Type	Text
Resource Type	Article

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