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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16187
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dc.contributor.authorViswanathan, Sangeetha-
dc.date.accessioned2024-10-25T06:40:57Z-
dc.date.available2024-10-25T06:40:57Z-
dc.date.issued2022-
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/10068439-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16187-
dc.description.abstractIncreasing 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.isoenen_US
dc.publisherIEEEen_US
dc.subjectComputer Scienceen_US
dc.subjectAnt colony optimizationen_US
dc.subjectFruit fly optimization algorithmen_US
dc.subjectGreen vehicle routing problemen_US
dc.subjectPheromone gainen_US
dc.titleA Hybrid Gain-Ant Colony Algorithm for Green Vehicle Routing Problemen_US
dc.typeArticleen_US
Appears in Collections:Department of Computer Science and Information Systems

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