Multiobjective Vehicle Routing Problem with Route Balance Based on Genetic Algorithm | Zendy

Wei Zhou | Zendy; Tingxin Song | Zendy; Fei He | Zendy; Liu Xi | Zendy

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Multiobjective Vehicle Routing Problem with Route Balance Based on Genetic Algorithm

Author(s) -

Wei Zhou,

Tingxin Song,

Fei He,

Liu Xi

Publication year - 2013

Publication title -

discrete dynamics in nature and society

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.264

H-Index - 39

eISSN - 1607-887X

pISSN - 1026-0226

DOI - 10.1155/2013/325686

Subject(s) - crossover , vehicle routing problem , benchmark (surveying) , genetic algorithm , computer science , selection (genetic algorithm) , mathematical optimization , tournament selection , point (geometry) , routing (electronic design automation) , balance (ability) , chromosome , mutation , algorithm , mathematics , artificial intelligence , computer network , medicine , biochemistry , chemistry , geometry , geodesy , physical medicine and rehabilitation , gene , geography

This study proposes a genetic algorithm to solve the biobjective vehicle routing problem with time windows simultaneously considering total distance and distance balance of active vehicle fleet. A new complex chromosome is used to present the active vehicle route. Through tournament selection, one-point crossover, and migrating mutation operator, the solution of the problem is solved. In experiment on Solomon's benchmark problems, considering the total distance and distance balance, the results are improved in all classes of problems. According to the experimental results, the suggested approach is sufficient and the average GA performance is good. © 2013 Wei Zhou et al.

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