An Empirical performances comparison of meta-heuristic algorithms for school bus routing problem

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dc.contributor.authorSemba, Sherehe
dc.contributor.authorMujuni, Egbert
dc.date.accessioned2021-05-12T11:54:05Z
dc.date.available2021-05-12T11:54:05Z
dc.date.issued2017
dc.descriptionPaper presented at the 4th Strathmore International Mathematics Conference (SIMC 2017), 19 - 23 June 2017, Strathmore University, Nairobi, Kenya.en_US
dc.description.abstractSchool Bus Routing Problem is an NP-hard Combinatorial Optimization problem, and hence solving the School Bus Routing Problem, requires the application of one or more of the metaheuristic algorithms. This work presents a model of the School Bus Routing Problem and empirical performances comparison between three meta- heuristic algorithms namely, Simulated Annealing, Tabu Search and Ant Colony for solving a real-life School Bus Routing Problem. We have analyzed their performances in terms of computation time, efficiency and solution quality. All the three algorithms have effectively demonstrated the ability to solve the School Bus Routing Problem. The computational results show that better solution quality and fastest execution time of the Meta-heuristic algorithms depends on the number of buses and stops. The results also show that Ant Colony Algorithm produces better solution, followed by Simulated Annealing, then Tabu Search for those schools with a large number of buses and stops.en_US
dc.description.sponsorshipDar es Salaam University College of Educationen_US
dc.identifier.urihttp://hdl.handle.net/11071/11866
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectSchool bus routing problemen_US
dc.subjectCombinatorial optimizationen_US
dc.subjectMeta-heuristic algorithmsen_US
dc.titleAn Empirical performances comparison of meta-heuristic algorithms for school bus routing problemen_US
dc.typeArticleen_US
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