A survey on multi-objective evolutionary algorithms for the solution of the environmental/economic dispatch problems

Development of efficient multi-objective evolutionary algorithms (MOEAs) has provided effective tools to solve environmental/economic dispatch (EED) problems. EED is a highly constrained complex bi-objective optimization problem. Since 1990s, numerous publications have reported the applications of M...

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Bibliographic Details
Published in:	Swarm and evolutionary computation Vol. 38; pp. 1 - 11
Main Authors:	Qu, B.Y., Zhu, Y.S., Jiao, Y.C., Wu, M.Y., Suganthan, P.N., Liang, J.J.
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.02.2018
Subjects:	Electric vehicles Environmental economic dispatch (EED) Evolutionary algorithms (EAs) Multi-objective evolutionary algorithms (MOEAs) Multi-objective optimization Wind power Evolutionary algorithms (EAs) Electric vehicles Multi-objective optimization Multi-objective evolutionary algorithms (MOEAs) Wind power Environmental economic dispatch (EED)
ISSN:	2210-6502
Online Access:	Get full text
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Summary:	Development of efficient multi-objective evolutionary algorithms (MOEAs) has provided effective tools to solve environmental/economic dispatch (EED) problems. EED is a highly constrained complex bi-objective optimization problem. Since 1990s, numerous publications have reported the applications of MOEAs to solve the EED problems. This paper surveys the state-of-the-art of research related to this direction. It covers topics of typical MOEAs, classical EED problems, Dynamic EED problems, EED problems incorporating wind power, EED problems incorporating electric vehicles and EED problems within micro-grids. In addition, some potential directions for future research are also presented.
ISSN:	2210-6502
DOI:	10.1016/j.swevo.2017.06.002