An Overview of Evolutionary Algorithms in Multiobjective Optimization

Abstract

The application of evolutionary algorithms in multiobjective optimization, proposed relatively early in their history, is currently receiving growing interest from researchers with various backgrounds. The paper reviews and discusses current multiobjective evolutionary approaches, identifying some of the issues raised by how they handle multi objectives, such as, how they effect the fitness landscape. Directions for future research are identified from the discussion.

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Authors/Creators:	Carlos, M. Fonseca Fleming, P.J.
Copyright, Publisher and Additional Information:	The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
Keywords:	Evolutionary algorithms, multi objective optimization, fitness assignment, search strategies, bibliography.
Dates:	Published: 15 July 1994
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) > ACSE Research Reports
Depositing User:	MRS ALISON THERESA BARNETT
Date Deposited:	17 Jul 2014 08:57
Last Modified:	24 Oct 2016 16:08
Status:	Published
Publisher:	Department of Automatic Control and Systems Engineering
Series Name:	ACSE Research Report 527

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An Overview of Evolutionary Algorithms in Multiobjective Optimization

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