Applying Quantum Computing to Solve Multicommodity Network Flow Problem

Fuente: arXiv
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Main Authors: Chence, Niu, Rastogi, Purvi, Soman, Jaikishan, Tamuli, Kausik, Dixit, Vinayak V.
Format: Preprint
Published: 2024
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author Chence, Niu
Rastogi, Purvi
Soman, Jaikishan
Tamuli, Kausik
Dixit, Vinayak V.
author_facet Chence, Niu
Rastogi, Purvi
Soman, Jaikishan
Tamuli, Kausik
Dixit, Vinayak V.
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2402_04758
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Applying Quantum Computing to Solve Multicommodity Network Flow Problem
Chence, Niu
Rastogi, Purvi
Soman, Jaikishan
Tamuli, Kausik
Dixit, Vinayak V.
Optimization and Control
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.
title Applying Quantum Computing to Solve Multicommodity Network Flow Problem
topic Optimization and Control
url https://arxiv.org/abs/2402.04758