Provably High-Quality Solutions for the Meal Delivery Routing Problem

Baris Yildiz () and Martin Savelsbergh ()
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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

Transportation Science, 2019, vol. 53, issue 5, 1372-1388

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.

Keywords: crowd logistics; last-mile logistics; on-demand meal delivery; dynamic vehicle routing; integer programming; column and row generation (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:53:y:2019:i:5:p:1372-1388

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