Mohit Kumar Kakkar,Neha Garg,Gourav Gupta,




Vehicle routing Problem,Fuel consumption,Genetic Algorithm,K-Means clustering,


Over the past few years, there has been increased awareness about the importance of protecting the environment particularly after global warming came up. The approach proposed here in this paper for reducing fuel consumption is the combination of clustering algorithms’ ideas with natural optimization techniques, aimed at efficient route optimization of vehicles. It uses clustering to group customer locations together that in turn allows the development of more efficient routes. The goal of this study is to reduce fuel consumption while optimizing travel plans. This study proposed a nature-inspired algorithm-based model for minimizing fuel consumption in the vehicle routing problem. K-means clustering and the genetic algorithm have been used in this study to find the optimized route with the minimum fuel consumption. It has been observed in this study that routing plans found by the proposed approach consume fewer units of fuel than those generated using optimization techniques which optimize distance covered. This indicates that such an approach could serve as a tool for minimizing fuel consumption in different enterprises.


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