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dc.contributor.authorBiswas, Sanjib
dc.date.accessioned2017-03-16T15:32:11Z
dc.date.available2017-03-16T15:32:11Z
dc.identifier.urihttp://hdl.handle.net/10464/11528
dc.description.abstractEfficient routing and scheduling has significant economic implications for many real-world situations arising in transportation logistics, scheduling, and distribution systems, among others. This work considers both the single depot vehicle routing problem with time windows (VRPTW) and the multi-depot vehicle routing problem with time windows (MDVRPTW). An age-layered population structure genetic algorithm is proposed for both variants of the vehicle routing problem. To the best of the author’s knowledge, this is first work to provide a multi-objective genetic algorithm approach for the MDVRPTW using well-known benchmark data with up to 288 customers.en_US
dc.language.isoengen_US
dc.publisherBrock Universityen_US
dc.subjectVehicle Routing Problemen_US
dc.subjectGenetic Algorithms
dc.subjectAge-layered Population Structure
dc.subjectMulti-objective GA
dc.titleMulti-objective Genetic Algorithms for Multi-depot VRP with Time Windowsen_US
dc.typeElectronic Thesis or Dissertationen_US
dc.degree.nameM.Sc. Computer Scienceen_US
dc.degree.levelMastersen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.degree.disciplineFaculty of Mathematics and Scienceen_US


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