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A Hybrid Gain-Ant Colony Algorithm for Green Vehicle Routing Problem

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dc.contributor.author Viswanathan, Sangeetha
dc.date.accessioned 2024-10-25T06:40:57Z
dc.date.available 2024-10-25T06:40:57Z
dc.date.issued 2022
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/10068439
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16187
dc.description.abstract Increasing carbon emissions, and thus footprint, is one of the main reasons for the imbalance in environmental sustainability, which is primarily contributed to transportation. Transportation is a core functionality of logistics distribution and supply chain. In this paper, a hybrid gain-ant colony optimization and fruit fly optimization algorithm for green vehicle routing problem is proposed to plan shortest paths with reduced total fuel consumption efficiently. The proposed algorithm was simulated using the Erdogan and Miller Hooks dataset and compared with best-known solutions and existing methods. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Computer Science en_US
dc.subject Ant colony optimization en_US
dc.subject Fruit fly optimization algorithm en_US
dc.subject Green vehicle routing problem en_US
dc.subject Pheromone gain en_US
dc.title A Hybrid Gain-Ant Colony Algorithm for Green Vehicle Routing Problem en_US
dc.type Article en_US


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