Modeling routing problems in QUBO with application to ride-hailing

• URL: http://arxiv.org/abs/2212.04894v1
• Date: Fri, 9 Dec 2022 14:55:34 GMT
• Title: Modeling routing problems in QUBO with application to ride-hailing
• Authors: Michele Cattelan and Sheir Yarkoni
• Abstract summary: We focus on one such routing problem, the Ride Pooling Problem (RPP), where multiple customers can request on-demand pickups and drop-offs from shared vehicles within a fleet. The task is to optimally pool customer requests using the limited set of vehicles, akin to a small-scale flexible bus route.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Many emerging commercial services are based on the sharing or pooling of resources for common use with the aim of reducing costs. Businesses such as delivery-, mobility-, or transport-as-a-service have become standard in many parts of the world, fulfilling on-demand requests for customers in live settings. However, it is known that many of these problems are NP-hard, and therefore both modeling and solving them accurately is a challenge. Here we focus on one such routing problem, the Ride Pooling Problem (RPP), where multiple customers can request on-demand pickups and drop-offs from shared vehicles within a fleet. The combinatorial optimization task is to optimally pool customer requests using the limited set of vehicles, akin to a small-scale flexible bus route. In this work, we propose a quadratic unconstrained binary optimization (QUBO) program and introduce efficient formulation methods for the RPP to be solved using metaheuristics, and specifically emerging quantum optimization algorithms.

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