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dc.contributor.authorAsobiela, Stephen Yamzuuga
dc.date.accessioned2013-09-12T13:03:38Z
dc.date.available2013-09-12T13:03:38Z
dc.date.issued2013-09-12
dc.identifier.urihttp://hdl.handle.net/10464/4985
dc.description.abstractHub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.en_US
dc.language.isoengen_US
dc.publisherBrock Universityen_US
dc.subjectGenetic Algorithms, Multi-Objective, Pareto Ranking, Sum of Ranks, Hub Location Problem, Weighted Sumen_US
dc.titleMulti-Objective Genetic Algorithms for the Single Allocation Hub Location Problemen_US
dc.typeElectronic Thesis or Dissertationen
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
dc.embargo.termsNoneen_US
refterms.dateFOA2021-08-03T02:23:30Z


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