A Comparative Study of Simulated Annealing and Genetic Algorithm for Solving the Travelling Salesman Problem

dc.contributor.authorOtubamowo, K.
dc.contributor.authorEgunjobi, T.O.
dc.contributor.authorAdewole, A.P.
dc.date.accessioned2019-09-11T10:08:42Z
dc.date.available2019-09-11T10:08:42Z
dc.date.issued2012-10
dc.descriptionStaff publicationen_US
dc.description.abstractMetaheuristic algorithms have proved to be good solvers for the traveling salesman problem (TSP). All metaheuristics usually encounter problems on which they perform poorly so the programmer must gain experience on which optimizers work well in different classes of problems. However due to the unique functionality of each type of meta-heuristic, comparison of metaheuristics is in many ways more difficult than other algorithmic comparisons. In this paper, solution to the traveling salesman problem was implemented using genetic algorithm and simulated annealing. These algorithms were compared based on performance and results using several benchmarks. It was observed that Simulated Annealing runs faster than Genetic Algorithm and runtime of Genetic Algorithm increases exponentially with number of cities. However, in terms of solution quality Genetic Algorithm is better than Simulated Annealing.en_US
dc.identifier.citationAdewole, A.P., Otubamowo, K., Egunjobi, T.O. (2012). A Comparative Study of Simulated Annealing and Genetic Algorithm for Solving the Travelling Salesman Problem. International Journal of Applied Information Systems (IJAIS), Vol.4(4):6-12pp.en_US
dc.identifier.issn2249-0868
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/5486
dc.language.isoenen_US
dc.publisherInternational Journal of Applied Information Systems (IJAIS)en_US
dc.relation.ispartofseriesInternational Journal of Applied Information Systems (IJAIS);Vol.4(4)
dc.subjectGenetic Algorithmen_US
dc.subjectSimulated Annealingen_US
dc.subjectTravelling Salesman Problemen_US
dc.subjectCandidate solutionen_US
dc.subjectOptimization problem.en_US
dc.subjectResearch Subject Categories::TECHNOLOGY::Information technology::Computer science::Computer scienceen_US
dc.titleA Comparative Study of Simulated Annealing and Genetic Algorithm for Solving the Travelling Salesman Problemen_US
dc.typeArticleen_US
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