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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16186
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dc.contributor.authorViswanathan, Sangeetha-
dc.date.accessioned2024-10-25T06:38:13Z-
dc.date.available2024-10-25T06:38:13Z-
dc.date.issued2023-
dc.identifier.urihttps://link.springer.com/referenceworkentry/10.1007/978-981-19-8851-6_6-1-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16186-
dc.description.abstractVehicle Routing Problem is one of the classical NP hard and combinatorial optimization problems that has been a spark of interest in the operation research domain. Though many variations of classical VRP are being developed, there is still the need for developing algorithms to improve solutions for VRP. A hybrid gain-based ant colony optimization-firefly algorithm (GACO-FA) has been proposed to deal with VRP. A global search is initially performed using the gain-based ant colony optimization, and subsequently local search for promising solution is done in the fine-tuned search space using firefly algorithm. The strengths of GACO and weakness of FA are aptly managed with a finer trade-off between them. The proposed GACO-FA is compared with best-known solutions and existing algorithms for performance analysis using the benchmark dataset. Analysis has been performed using measures like route cost, standard deviation, and percentage variation in length. The results have also been statistically verified for their significance.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectComputer Scienceen_US
dc.subjectGACO-FAen_US
dc.subjectAlgorithmsen_US
dc.subjectVehicle Routing Problemen_US
dc.titleSolving Vehicle Routing Problem Using a Hybridization of Gain-Based Ant Colony Optimization and Firefly Algorithmsen_US
dc.typeBook chapteren_US
Appears in Collections:Department of Computer Science and Information Systems

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