A genetic ant colony optimization approach for concave cost transportation problemsac

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dc.contributor.authorAltıparmak, Fulya
dc.contributor.authorKaraoğlan, İsmail
dc.date.accessioned2020-03-26T17:16:55Z
dc.date.available2020-03-26T17:16:55Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.descriptionIEEE Congress on Evolutionary Computation -- SEP 25-28, 2007 -- Singapore, SINGAPOREen_US
dc.description.abstractThe concave cost transportation problem (ccTP) is one of the practical distribution and logistics problems. The ccTP arises when the unit cost for transporting products decreases as the amount of products increases. Generally, these costs are modeled as nonlinear, especially concave. Since the ccTP is NP-hard, solving large-scale problems is time-consuming. In this paper, we propose a hybrid search algorithm based on genetic algorithms (GA) and ant colony optimization (ACO) to solve the ccTP. This algorithm, called h_GACO, is a GA supplemented with ACO in where ACO is implemented to exploit information stored in pheromone trails during genetic operations, i.e. crossover and mutation. The effectiveness of h_GACO is investigated comparing its results with those obtained by five different metaheuristic approaches given in the literature for the ccTP.en_US
dc.description.sponsorshipIEEEen_US
dc.description.sponsorshipGazi University as Scientific Research [06/200640]en_US
dc.description.sponsorshipThis research is supported by Gazi University as Scientific Research Project (No. 06/200640)en_US
dc.identifier.doi10.1109/CEC.2007.4424676en_US
dc.identifier.endpage+en_US
dc.identifier.isbn978-1-4244-1339-3
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1685en_US
dc.identifier.urihttps://dx.doi.org/10.1109/CEC.2007.4424676
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21169
dc.identifier.wosWOS:000256053701038en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGSen_US
dc.relation.ispartofseriesIEEE Congress on Evolutionary Computation
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleA genetic ant colony optimization approach for concave cost transportation problemsacen_US
dc.typeConference Objecten_US

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