Order Assignment and Routing Optimization for Crowdsourced Food Delivery with Time Windows

DOI

10.2991/978-94-6463-958-2_27How to use a DOI?

Keywords

Crowdsourced food delivery; Order assignment; Routing optimization; Meal preparation time; Rolling optimization

Abstract

With the rapid growth of real-time delivery demand, the food delivery industry faces challenges like concentrated orders, insufficient capacity, and peak-hour delays. Crowdsourcing eases platform pressure but brings complexities such as random orders, uncertain meal prep times, and dynamic rider states. This paper proposes a unified order assignment and routing model (considering meal prep time) and a hybrid rolling-horizon optimization framework, aiming to minimize total costs (travel, lateness penalty, waiting, fixed rider costs). Static and dynamic simulations validate its effectiveness in improving efficiency, reducing lateness, and ensuring adaptability^[1].

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xin Liu
PY  - 2025
DA  - 2025/12/26
TI  - Order Assignment and Routing Optimization for Crowdsourced Food Delivery with Time Windows
BT  - Proceedings of the 5th International Conference on Management Science and Software Engineering (ICMSSE 2025)
PB  - Atlantis Press
SP  - 241
EP  - 248
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-958-2_27
DO  - 10.2991/978-94-6463-958-2_27
ID  - Liu2025
ER  -