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Integrated Online Order Picking and Vehicle Routing of Food Cold Chain with Demand Surge

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  • Youhua Chen
  • Hongjie Lan
  • Chuan Wang
  • Xiaoqiong Jia
  • Laxminarayan Sahoo

Abstract

This paper focuses on the effect of demand surge on the food cold chain, where orders arrive online. The demand surge has successively affected the order batching, batch sequencing, and route planning, compared to regular demand. This research studies the integrated optimization of food cold chain order picking and vehicle routing of online orders, where mixed integer programming model is formulated to minimize time-consuming and cost. We firstly use K-means++ algorithm to cluster all customers, and then an online batch processing algorithm is designed in each region. Finally, a genetic algorithm is used to complete the joint optimization of the picking and delivery. We use X enterprise’s e-commerce platform as a case to collect actual operating data to verify the effectiveness of the model and algorithm. And comparing the analysis results between phased optimization and integrated optimization, reasonable suggestions are put forward for management decisions.

Suggested Citation

  • Youhua Chen & Hongjie Lan & Chuan Wang & Xiaoqiong Jia & Laxminarayan Sahoo, 2022. "Integrated Online Order Picking and Vehicle Routing of Food Cold Chain with Demand Surge," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-14, July.
    • Handle: RePEc:hin:jnlmpe:4485376
    DOI: 10.1155/2022/4485376
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    Cited by:

    1. Kaibo Liang & Li Zhou & Jianglong Yang & Huwei Liu & Yakun Li & Fengmei Jing & Man Shan & Jin Yang, 2023. "Research on a Dynamic Task Update Assignment Strategy Based on a “Parts to Picker” Picking System," Mathematics, MDPI, vol. 11(7), pages 1-29, March.

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