Hybrid Quantum Tabu Search for Solving the Vehicle Routing Problem

TL;DR

This paper introduces a hybrid quantum-classical metaheuristic algorithm for the Capacitated Vehicle Routing Problem, demonstrating its ability to often outperform existing hybrid methods in finding optimal solutions.

Contribution

The paper presents a novel hybrid quantum-classical algorithm specifically designed for the CVRP, improving solution quality over previous hybrid approaches.

Findings

The proposed algorithm often finds the best-known solutions.

It outperforms other hybrid quantum-classical approaches.

Experimental results validate its effectiveness.

Abstract

There has never been a more exciting time for the future of quantum computing than now. Near-term quantum computing usage is now the next XPRIZE. With that challenge in mind we have explored a new approach as a hybrid quantum-classical algorithm for solving NP-Hard optimization problems. We have focused on the classic problem of the Capacitated Vehicle Routing Problem (CVRP) because of its real-world industry applications. Heuristics are often employed to solve this problem because it is difficult. In addition, meta-heuristic algorithms have proven to be capable of finding reasonable solutions to optimization problems like the CVRP. Recent research has shown that quantum-only and hybrid quantum/classical approaches to solving the CVRP are possible. Where quantum approaches are usually limited to minimal optimization problems, hybrid approaches have been able to solve more significant problems. Still, the hybrid approaches often need help finding solutions as good as their classical counterparts. In our proposed approach, we created a hybrid quantum/classical metaheuristic algorithm capable of finding the best-known solution to a classic CVRP problem. Our experimental results show that our proposed algorithm often outperforms other hybrid approaches.