Transit facility allocation: Hybrid quantum-classical optimization

TL;DR

This paper introduces a hybrid quantum-classical optimization framework for transit facility planning that balances efficiency and accessibility, demonstrated by reducing facilities by 40% without sacrificing service quality.

Contribution

It presents a novel mathematical model integrating quantum effects and GIS data for transit facility consolidation, enabling the use of advanced quantum hardware in urban planning.

Findings

Reduced the number of transit facilities by 40% while maintaining accessibility

Effectively utilized quantum annealing and classical optimization techniques

Applied framework to Vancouver's transit system with successful results

Abstract

An essential consideration in urban transit facility planning is service efficiency and accessibility. Previous research has shown that reducing the number of facilities along a route may increase efficiency but decrease accessibility. Striking a balance between these two is a critical consideration in transit planning. Transit facility consolidation is a cost-effective way to improve the quality of service by strategically determining the desirable allocation of a limited number of facilities. This paper develops an optimization framework that integrates Geographical Information systems (GIS), decision-making analysis, and quantum technologies for addressing the problem of facility consolidation. Our proposed framework includes a novel mathematical model that captures non-linear interactions between facilities and surrounding demand nodes, inter-facility competition, ridership demand and spatial coverage. The developed model can harness the power of quantum effects such as superposition and quantum tunnelling and enables transportation planners to utilize the most recent hardware solutions such as quantum and digital annealers, coherent Ising Machines and gate-based universal quantum computers. This study presents a real-world application of the framework to the public transit facility redundancy problem in the British Columbia Vancouver metropolitan area. We demonstrate the effectiveness of our framework by reducing the number of facilities by 40% while maintaining the same service accessibility. Additionally, we showcase the ability of the proposed mathematical model to take advantage of quantum annealing and classical optimization techniques.