Data Structures in Multi-Objective Evolutionary Algorithms

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書誌詳細
出版年:	Journal of Computer Science and Technology vol. 27, no. 6 (Nov 2012), p. 1197
第一著者:	Altwaijry, Najwa
その他の著者:	El Bachir Menai, Mohamed
出版事項:	Springer Nature B.V.
主題:	Mathematical programming Search process Population Computer science Analysis Populations Studies Data structures Genetic algorithms Optimization Generations Archives & records Pareto optimization Hierarchies Multiple objective analysis Pareto optimum Evolutionary algorithms Information science
オンライン･アクセス:	Citation/Abstract Full Text - PDF
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その他の書誌記述
抄録:	Data structures used for an algorithm can have a great impact on its performance, particularly for the solution of large and complex problems, such as multi-objective optimization problems (MOPs). Multi-objective evolutionary algorithms (MOEAs) are considered an attractive approach for solving MOPs, since they are able to explore several parts of the Pareto front simultaneously. The data structures for storing and updating populations and non-dominated solutions (archives) may affect the efficiency of the search process. This article describes data structures used in MOEAs for realizing populations and archives in a comparative way, emphasizing their computational requirements and general applicability reported in the original work.[PUBLICATION ABSTRACT]
ISSN:	1000-9000 1860-4749
DOI:	10.1007/s11390-012-1296-y
ソース:	ABI/INFORM Global