A Modified Kruskal's Algorithm to Improve Genetic Search for Open Vehicle Routing Problem

被引:13
作者
Dutta, Joydeep [1 ]
Barma, Partha Sarathi [1 ]
Kar, Samarjit [2 ]
De, Tanmay [1 ]
机构
[1] Natl Inst Technol Durgapur, Durgapur, W Bengal, India
[2] Natl Inst Technol Durgapur, Dept Math, Durgapur, W Bengal, India
关键词
Evolutionary Computation; Genetic Algorithms; Road Transportation; Shortest Path Problem; Vehicle Routing; TABU SEARCH; NEIGHBORHOOD SEARCH; ANT COLONY; BACKHAULS; CROSSOVER;
D O I
10.4018/IJBAN.2019010104
中图分类号
F [经济];
学科分类号
02 ;
摘要
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.
引用
收藏
页码:55 / 76
页数:22
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