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Solving Vehicle Routing Problem Using a Hybridization of Gain-Based Ant Colony Optimization and Firefly Algorithms

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dc.contributor.author Viswanathan, Sangeetha
dc.date.accessioned 2024-10-25T06:38:13Z
dc.date.available 2024-10-25T06:38:13Z
dc.date.issued 2023
dc.identifier.uri https://link.springer.com/referenceworkentry/10.1007/978-981-19-8851-6_6-1
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16186
dc.description.abstract Vehicle 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.iso en en_US
dc.publisher Springer en_US
dc.subject Computer Science en_US
dc.subject GACO-FA en_US
dc.subject Algorithms en_US
dc.subject Vehicle Routing Problem en_US
dc.title Solving Vehicle Routing Problem Using a Hybridization of Gain-Based Ant Colony Optimization and Firefly Algorithms en_US
dc.type Book chapter en_US


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