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Provably High-Quality Solutions for the Meal Delivery Routing Problem

Author

Listed:
  • Baris Yildiz

    (Department of Industrial Engineering, Koc University, 34450 Istanbul, Turkey)

  • Martin Savelsbergh

    (H. Milton Stewart School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

Online restaurant aggregators with integrated meal delivery networks have become more common and more popular in the past few years. Meal delivery is arguably the ultimate challenge in last-mile logistics: a typical order is expected to be delivered within an hour (much less if possible) and within minutes of the food becoming ready. We introduce a novel formulation for a meal delivery routing problem (in which we assume perfect information about order arrivals) and develop a simultaneous column- and row-generation method for its solution. The analysis of the results of an extensive computational study, using instances derived from real-life data, demonstrates the efficacy of the solution approach, and provides valuable insights into, among others, the (potential) benefits of order bundling, courier-shift scheduling, and demand management.

Suggested Citation

  • Baris Yildiz & Martin Savelsbergh, 2019. "Provably High-Quality Solutions for the Meal Delivery Routing Problem," Transportation Science, INFORMS, vol. 53(5), pages 1372-1388, September.
    • Handle: RePEc:inm:ortrsc:v:53:y:2019:i:5:p:1372-1388
    DOI: 10.1287/trsc.2018.0887
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    References listed on IDEAS

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    2. Xiaotong Guo & Yong He, 2022. "Mathematical Modeling and Optimization of Platform Service Supply Chains: A Literature Review," Mathematics, MDPI, vol. 10(22), pages 1-19, November.
    3. Liu, Yang & Li, Sen, 2023. "An economic analysis of on-demand food delivery platforms: Impacts of regulations and integration with ride-sourcing platforms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 171(C).
    4. Chen, Linlin & Han, Shuihua & Ye, Zhen & Xia, Senmao, 2023. "The optimisation of the location of front distribution centre: A spatio-temporal joint perspective," International Journal of Production Economics, Elsevier, vol. 263(C).
    5. Long He & Sheng Liu & Zuo‐Jun Max Shen, 2022. "Smart urban transport and logistics: A business analytics perspective," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3771-3787, October.
    6. Hao, Peng & Liu, Haishan & Liao, Yejia & Boriboonsomsin, Kanok & Barth, Matthew J, 2022. "Developing Environmentally Friendly Solutions for On-Demand Food Delivery Service," Institute of Transportation Studies, Working Paper Series qt89c461pv, Institute of Transportation Studies, UC Davis.
    7. Auad, Ramon & Erera, Alan & Savelsbergh, Martin, 2023. "Courier satisfaction in rapid delivery systems using dynamic operating regions," Omega, Elsevier, vol. 121(C).
    8. Wenjie Wang & Lei Xie, 2022. "Optimal pricing of crowdsourcing logistics services with social delivery capacity," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1447-1469, July.

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