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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2402.04758 |
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| _version_ | 1866917584295690240 |
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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 |