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Open AccessArticle

Vehicle Routing Optimization of Instant Distribution Routing Based on Customer Satisfaction

by Yan Zhang 1, Chunhui Yuan 1 and Jiang Wu 2,*
1
School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China
2
School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China
*
Author to whom correspondence should be addressed.
Information 2020, 11(1), 36; https://doi.org/10.3390/info11010036
Received: 4 December 2019 / Revised: 31 December 2019 / Accepted: 6 January 2020 / Published: 9 January 2020
Since the actual factors in the instant distribution service scenario are not considered enough in the existing distribution route optimization, a route optimization model of the instant distribution system based on customer time satisfaction is proposed. The actual factors in instant distribution, such as the soft time window, the pay-to-order mechanism, the time for the merchant to prepare goods before delivery, and the deliveryman’s order combining, were incorporated in the model. A multi-objective optimization framework based on the total cost function and time satisfaction of the customer was established. Dual-layer chromosome coding based on the deliveryman-to-node mapping and the access order was conducted, and the nondominated sorting genetic algorithm version II (NSGA-II) was used to solve the problem. According to the numerical results, when time satisfaction of the customer was considered in the instant distribution routing problem, the customer satisfaction increased effectively and the balance between customer satisfaction and delivery cost in the means of Pareto optimization were obtained, with a minor increase in the delivery cost, while the number of deliverymen slightly increased to meet the on-time delivery needs of customers. View Full-Text
Keywords: logistics distribution; distribution routing optimization; vehicle routing problems; multi-objective optimization; customer satisfaction; nondominated sorting genetic algorithm version II (NSGA-II) logistics distribution; distribution routing optimization; vehicle routing problems; multi-objective optimization; customer satisfaction; nondominated sorting genetic algorithm version II (NSGA-II)
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Zhang, Y.; Yuan, C.; Wu, J. Vehicle Routing Optimization of Instant Distribution Routing Based on Customer Satisfaction. Information 2020, 11, 36.

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