QUEST: QUantum-Enhanced Shared Transportation

TL;DR

This paper introduces QUEST, a quantum-enhanced framework for solving large-scale shared transportation matching problems by translating them into quantum-optimized models, demonstrating successful classical and quantum solution approaches on a prototype.

Contribution

It formulates the WaaS matching problem as a MIQP and QUBO, enabling quantum algorithms to potentially improve large-scale transportation optimization.

Findings

Classical methods verified the prototype solutions.

Quantum algorithms successfully recovered classical optimal solutions.

The framework sets the stage for quantum advantage in transportation problems.

Abstract

We introduce ``Windbreaking-as-a-Service'' (WaaS) as an innovative approach to shared transportation in which larger ``windbreaker'' vehicles provide aerodynamic shelter for ``windsurfer'' vehicles, thereby reducing drag and fuel consumption. As a computational framework to solve the large-scale matching and assignment problems that arise in WaaS, we present \textbf{QUEST} (Quantum-Enhanced Shared Transportation). Specifically, we formulate the pairing of windbreakers and windsurfers -- subject to timing, speed, and vehicle-class constraints -- as a mixed-integer quadratic problem (MIQP). Focusing on a single-segment prototype, we verify the solution classically via the Hungarian Algorithm, a Gurobi-based solver, and brute-force enumeration of binary vectors. We then encode the problem as a Quadratic Unconstrained Binary Optimization (QUBO) and map it to an Ising Hamiltonian, enabling the use of the Quantum Approximate Optimization Algorithm (QAOA) and other quantum and classical annealing technologies. Our quantum implementation successfully recovers the optimal assignment identified by the classical methods, confirming the soundness of the QUEST pipeline for a controlled prototype. While QAOA and other quantum heuristics do not guarantee a resolution of the fundamental complexity barriers, this study illustrates how the WaaS problem can be systematically translated into a quantum-ready model. It also lays the groundwork for addressing multi-segment scenarios and potentially leveraging quantum advantage for large-scale shared-transportation instances.