Applying Quantum Computing to Solve Multicommodity Network Flow Problem

TL;DR

This paper investigates the application of quantum annealing to solve the NP-hard multicommodity network flow problem, comparing its performance with traditional methods in terms of solution quality and efficiency.

Contribution

It introduces a quantum computing approach to address the MCNF problem and evaluates its potential advantages over classical methods.

Findings

Quantum annealing shows promise for large-scale transportation problems.

Quantum approach achieves comparable or better solutions faster.

Potential for quantum computing to revolutionize logistics optimization.

Abstract

In this paper, the multicommodity network flow (MCNF) problem is formulated as a mixed integer programing model which is known as NP-hard, aiming to optimize the vehicle routing and minimize the total travel cost. We explore the potential of quantum computing, specifically quantum annealing, by comparing its performance in terms of solution quality and efficiency against the traditional method. Our findings indicate that quantum annealing holds significant promise for enhancing computation in large-scale transportation logistics problems.