Power economic dispatch using a hybrid genetic algorithm
| dc.contributor.author | Yalcinoz T. | |
| dc.contributor.author | Altun H. | |
| dc.date.accessioned | 2019-08-01T13:38:39Z | |
| dc.date.available | 2019-08-01T13:38:39Z | |
| dc.date.issued | 2001 | |
| dc.department | Niğde ÖHÜ | |
| dc.description.abstract | This letter outlines a hybrid genetic algorithm (HGA) for solving the economic dispatch problem. The algorithm incorporates the solution produced by an improved Hopfield neural network (NN) [1] as a part of its initial population. Elitism, arithmetic crossover, and mutation are used in the GAs to generate successive sets of possible operating policies. The technique improves the quality of the solution and reduces the computation time, and is compared with the classical optimization technique, an improved Hopfield NN approach (IHN) [1], a fuzzy logic controlled GA (FLCGA) [2], and an improved GA (IGA) [3]. | |
| dc.identifier.doi | 10.1109/39.911360 | |
| dc.identifier.endpage | 60 | |
| dc.identifier.issn | 0272-1724 | |
| dc.identifier.issue | 3 | |
| dc.identifier.scopus | 2-s2.0-0035274988 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 59 | |
| dc.identifier.uri | https://dx.doi.org/10.1109/39.911360 | |
| dc.identifier.uri | https://hdl.handle.net/11480/1383 | |
| dc.identifier.volume | 21 | |
| dc.indekslendigikaynak | Scopus | |
| dc.institutionauthor | [0-Belirlenecek] | |
| dc.language.iso | en | |
| dc.relation.ispartof | IEEE Power Engineering Review | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Arithmetic crossover | |
| dc.subject | Economic dispatch | |
| dc.subject | HGA | |
| dc.subject | Hopfield neural networks | |
| dc.title | Power economic dispatch using a hybrid genetic algorithm | |
| dc.type | Article |
