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中国管理科学 ›› 2026, Vol. 34 ›› Issue (4): 178-191.doi: 10.16381/j.cnki.issn1003-207x.2024.1365cstr: 32146.14.j.cnki.issn1003-207x.2024.1365

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考虑履单地点选择及渠道资源共享的全渠道零售商定价和履单联合优化问题研究

邹璧林, 吕晓慧(), 张小洪   

  1. 苏州大学政治与公共管理学院,江苏 苏州 215003
  • 收稿日期:2024-08-13 修回日期:2025-05-11 出版日期:2026-04-25 发布日期:2026-03-27
  • 通讯作者: 吕晓慧 E-mail:xhlyu@suda.edu.cn
  • 基金资助:
    江苏省社会科学基金青年项目(23GLC012);国家自然科学基金青年项目(72401212);江苏省基础研究计划青年项目(BK20240755)

Joint Pricing and Fulfillment Optimization for Omni-channel Retailers Considering Fulfillment Location Selection and Resources Sharing among Channels

Bilin Zou, Xiaohui Lyu(), Xiaohong Zhang   

  1. School of Politics and Public Administration,Soochow University,Suzhou 215003,China
  • Received:2024-08-13 Revised:2025-05-11 Online:2026-04-25 Published:2026-03-27
  • Contact: Xiaohui Lyu E-mail:xhlyu@suda.edu.cn

摘要:

在全渠道零售背景下,零售商对线上及线下渠道定价及各项履单优化进行单独决策,导致线上线下难以发挥互补优势。基于此,针对全渠道零售商在各个销售周期及区域可选择履单中心与实体店进行流通加工的实际情形,且为了提高线上与线下渠道资源的利用效率,本文考虑履单地点选择及渠道资源共享的定价-履单决策联合优化问题,其中履单决策包括履单地点选择决策、库存决策、运输决策。首先,以全渠道零售商总利润最大化为目标,建立了全渠道零售商定价-履单决策联合优化混合整数非线性规划模型,并将该模型扩展至考虑线上与线下渠道资源共享情形;其次,针对模型高维复杂的特点,设计了协同进化算法以提升求解性能;最后,通过数值实验验证了算法的有效性。研究结果表明:定价决策与履单决策之间具有相关性,且在履单决策中考虑履单地点选择决策可显著提高全渠道零售商的总利润;线上与线下渠道的资源共享可有效降低履单成本,提高全渠道零售网络的总利润,且网络规模越大,总利润的提升越明显。

关键词: 定价和履单联合优化, 履单地点选择, 渠道资源共享, 全渠道零售, 协同进化算法

Abstract:

The omni-channel retail model reconstructs the way in which the traditional retail industry creates value online or offline. With the implementation of this model, a large number of retailers blindly imitate the business model and make separate decisions on online and offline channel pricing and fulfillment optimization, which makes it difficult for online and offline channels to exert complementary advantages. Therefore, in view of the actual situation that omni-channel retailers can choose fulfillment centers and physical stores to circulate and process goods in multi-period and multi-region, and in order to improve the utilization efficiency of online and offline channel resources, the joint optimization problem of pricing and fulfillment decision is studied considering fulfillment location selection and resource sharing among channels. Among them, the fulfillment decision includes fulfillment location selection decision, inventory decision and transportation decision. Focusing on research problem, a mixed integer nonlinear programming model for joint optimization of pricing and fulfillment decision of omni-channel retailers is established with the goal of maximizing the total profit of omni-channel retailers. Based on this model, an optimization model considering resources sharing among online and offline channels is established to further explore how to rationally allocate the resources of each channel. Then, a co-evolutionary algorithm is proposed to solve the model. Finally, the effectiveness of the co-evolutionary algorithm is verified by numerical experiments. The results show that: there is a correlation between pricing decision and fulfillment decision, and considering the fulfillment location selection in fulfillment decision can significantly improve the total profit of the omni-channel retailers; fully sharing and integrating resources among online and offline channels enables omni-channel retailers to make decisions that reduce fulfillment costs, thereby increasing the total profit of the omni-channel retail network, and the larger the network size, the more obvious the increase in the total profit of omni-channel retailers.

Key words: joint pricing and fulfillment optimization, fulfillment location selection, resources sharing among channels, omni-channel retail, co-evolutionary algorithm

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