Environmentally constrained economic dispatch via a genetic algorithm with arithmetic crossover

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dc.authorid0000-0002-2126-8757
dc.authorid0000-0002-8291-1419
dc.contributor.authorYalcinoz, T
dc.contributor.authorAltun, H
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2002
dc.departmentNiğde ÖHÜ
dc.description6th IEEE Africon Conference -- OCT 02-04, 2002 -- UNIV PRETORIA, GEORGE, SOUTH AFRICA
dc.description.abstractFor electric power generation and dispatching problems, absolute minimum cost is not any more the only criterion to be met. Environmental considerations have become one of the major management concerns. The environmentally constrained economic dispatch problem can be classified as a multi-objective optimization and non-linear programming problem. This paper proposes a solution for environmental economic dispatch problem using modified GA which based on arithmetic crossover operator. The employed arithmetic crossover operation takes the real values presented by two individuals and produced new generation on the basis of the arithmetic mean. Numerical results for two case studies have been presented to illustrate the performance and applicability of the proposed method.
dc.description.sponsorshipNRF, Cape Technikon, IEEE S Africa Sect, Reg 8, SAiEE
dc.identifier.endpage928
dc.identifier.isbn0-7803-7570-X
dc.identifier.scopus2-s2.0-0036992610
dc.identifier.scopusqualityN/A
dc.identifier.startpage923
dc.identifier.urihttps://hdl.handle.net/11480/5737
dc.identifier.wosWOS:000180673700171
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2002 IEEE AFRICON, VOLS 1 AND 2: ELECTROTECHNOLOGICAL SERVICES FOR AFRICA
dc.relation.ispartofseriesIEEE Africon
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleEnvironmentally constrained economic dispatch via a genetic algorithm with arithmetic crossover
dc.typeConference Object

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