Please use this identifier to cite or link to this item: http://dspace.uniten.edu.my/jspui/handle/123456789/377
DC FieldValueLanguage
dc.contributor.authorMohammed, M.A.en_US
dc.contributor.authorAhmad, M.S.en_US
dc.contributor.authorMostafa, S.A.en_US
dc.date.accessioned2017-07-25T03:16:38Z-
dc.date.available2017-07-25T03:16:38Z-
dc.date.issued2012-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84867954555&doi=10.1109%2fICCISci.2012.6297250&partnerID=40&md5=6e4cd28f948014242567fba5a1f7bce7-
dc.identifier.urihttp://dspace.uniten.edu.my:80/jspui/handle/123456789/377-
dc.description.abstractVehicle Routing Problem (VRP) has been considered as a significant segment in logistic handling. Thus, a proper selection of vehicle routes plays a very important part to ameliorate the economic benefits of logistic operations. In this paper, we consider the application of a Genetic Algorithm (GA) to a Capacitated Vehicle Routing Problem (CVRP) in which a set of vehicles with limits on capacity and travel time are available to service a set of customers and constrained by earliest and latest time for serving. The results of our test show that GA is able to determine the optimum route for the vehicles while maintaining their constraints of capacity and travel time. © 2012 IEEE.en_US
dc.language.isoenen_US
dc.subjectCapacitated Vehicle Routing Problemen_US
dc.subjectGenetic Algorithmen_US
dc.subjectOptimal routeen_US
dc.subjectVehicle Routing Problemen_US
dc.titleUsing genetic algorithm in implementing capacitated vehicle routing problemen_US
dc.typeConference Paperen_US
dc.relation.conference2012 International Conference on Computer and Information Scienceen_US
dc.identifier.doi10.1109/ICCISci.2012.6297250-
dc.identifier.scopus2-s2.0-84867954555-
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:CCI Scholarly Publication
Show simple item record

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.