Real-Time Delivery Routing Optimization Based on Customer Classification

Abstract

Abstract:

Real-time delivery enterprises can perform refined operations on customers under the background of big data. This paper aims to find a distribution strategy for real-time delivery enterprises, so that enterprises can obtain more potential benefits and achieve sustainable development with limited resources. The customer classification is incorporated into the problem of real-time distribution routing optimization, and the customers are divided into multiple levels based on the customer's consumption behavior. The overtime penalty cost is set according to the characteristics of customers at different levels. A mathematical model based on customer classification is established. And a genetic algorithm based on the characteristics of the real-time delivery routing problem is proposed. Finally, a real-time delivery enterprise business case is used to verify the effectiveness of the model and algorithm.

Key words: logistics engineering, vehicle routing problem, real-time delivery, genetic algorithm, customer classification

摘要：

大数据背景下即时配送平台对客户进行精细化管理已成为可能.为寻求企业长期发展，将客户分类融入到车辆路径问题中，用有限的资源提高配送准时性以得到优质客户的维持和发展，为企业赢得更多潜在效益.本文结合客户的消费行为将客户分为多个层级，根据每层级客户的特点设置超时惩罚成本，构建出基于客户分类的即时配送路径优化模型，并根据问题特点设计遗传算法求解，最后，结合某即时配送平台的业务场景进行案例分析，验证了模型和算法的有效性.

关键词: 物流工程, 车辆路径问题, 即时配送, 遗传算法, 客户分类

CLC Number:

V355.2

YU Jiang-xia, DU Hong-ya, LUO Tai-bo. Real-Time Delivery Routing Optimization Based on Customer Classification[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(4): 202-208.

于江霞，杜红亚，罗太波. 基于客户分类的即时配送路径优化研究[J]. 交通运输系统工程与信息, 2020, 20(4): 202-208.

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