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A Modified Kruskal's Algorithm to Improve Genetic Search for Open Vehicle Routing Problem
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Author(s): Joydeep Dutta (National Institute of Technology Durgapur, West Bengal, India), Partha Sarathi Barma (National Institute of Technology Durgapur, West Bengal, India), Samarjit Kar (National Institute of Technology Durgapur, West Bengal, India)and Tanmay De (National Institute of Technology Durgapur, West Bengal, India)
Copyright: 2021
Pages: 23
Source title:
Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-8048-6.ch021
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Abstract
This article has proposed a modified Kruskal's method to increase the efficiency of a genetic algorithm to determine the path of least distance starting from a central point to solve the open vehicle routing problem. In a vehicle routing problem, vehicles start from a central point and several customers placed in different locations to serve their demands and return to the central point. In the case of the open vehicle routing problem, the vehicles do not go back to the central point after serving the customers. The challenge is to reduce the number of vehicles used and the distance travelled simultaneously. The proposed method applies genetic algorithms to find the set of customers those are covered by a particular vehicle and the authors have applied the proposed modified Kruskal's method for local routing optimization. The results of the new method are analyzed in comparison with some of the evolutionary methods.
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