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基于极值—蚁群算法的电商末端物流弹性配送策略研究

  

  1. 1. 华中科技大学 自动化学院，湖北 武汉 430074；2. 湖北工业大学 理学院，湖北 武汉 430068
  • 出版日期:2016-02-29 发布日期:2016-04-05
  • 作者简介: 阮焕(1992-)，男，湖北省人，硕士研究生，主要研究方向为供应链管理、决策分析.
  • 基金资助:

    国家自然科学基金资助项目(71171089)

Ecommerce Ending Logistics Resilient Distribution Strategy Research Based on the Extreme Optimization—Ant Colony Algorithm

  1. 1. School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; 2. School of Science, Hubei University of Technology, Wuhan, Hubei 430068, China
  • Online:2016-02-29 Published:2016-04-05

摘要：

主要研究电商物流配送中货物由配送中心送达客户的过程，即末端物流。为降低配送成本同时提高服务质量，结合车辆路径问题与电商中消费需求“多品种、小批量、多批次、短周期”的特点，针对客户每日需求的不确定性，提出针对每日需求的信息化的弹性配送策略，以人均成本最小化为目标构造了模型；设计基于极值动力学的改进蚁群算法对物流配送路径进行优化，通过“寻优”与“弃差”、局部搜索与全局搜索相结合，提高了算法收敛效率；并通过对算例验证了该算法在面对多种不确定性需求时候的弹性，有助于实现电商物流的有效配送。

关键词: 电商末端物流, 极值动力学, 蚁群算法, 弹性配送

Abstract:

A study is conducted into the process called the ending logistics in which goods are delivered to customers from the distribution center in ecommerce logistics distribution. To reduce distribution cost and improve service quality, the vehicle routing problem is combined with the characteristics of ecommerce consumers′ demand, namely “big varieties, small quantity, multiple batches and short cycle”. Based on the uncertainty in customer daily demand, the informatization resilience distribution strategy is put forward. A model with the target of minimizing the per capita cost is established along with an improved ant colony algorithm based on the extreme dynamics to optimize the logistics distribution path. The convergence efficiency of the algorithm has been largely improved through the “optimization” and “elimination” and by combining “global search” with “local search”. Finally, an example is taken to verify the resilience of the algorithm faced with uncertainty demands. Effective distribution of ecommerce logistics can be achieved based on this research.

Key words: e-commerce ending logistics, extreme dynamics, ant colony algorithm, resilience distribution