Hongjun Zhu, Yangxin Teng, and Shuchang Xiao
County-level express delivery, improved genetic algorithm (IGA), multi-objective optimisation, multi-strategy integration
In this paper, a multi-objective vehicle path optimisation model with capacity constraints and time windows is proposed for the logistics and distribution problem of a single distribution center in a county city. The model comprehensively considers the objectives of enterprise cost, distribution efficiency, employee job satisfaction and customer satisfaction, and designs an improved genetic algorithm (IGA) incorporating multi-strategy to solve the problem. The IGA incorporating multi-strategy generates the initial population through an ant colony algorithm and combines the Bernoulli chaotic mapping operator, Gaussian operator and Sigmoid operator to improve the selection, crossover and mutation operations. The method of this paper is validated on the Solomon dataset and the real data of An’yue County, respectively. When compared with the comparison algorithms, the total distance travelled by all vehicles is reduced by a maximum of 63.10% and 34.37%. At the same time, the remaining loading margins of the vehicles were reduced by a maximum of 65.29% and 36.34%, respectively, and the maximum and minimum time difference between the work of the employees (T), was reduced by a maximum of 78.88% and 37.55%, respectively. The research work in this paper provides an efficient and intelligent solution for county urban express delivery and enriches the related field research.
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