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International Journal of Creative and Open Research in Engineering and Management

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ISSN: 3108-1754 (Online)
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Peer Review: Double Blind
Volume 02, Issue 8

Published on: August 2026

QUANTUM COMPUTING FOR LOGISTICS OPTIMIZATION: ANNEALING IN ULD CONFIGURATION AND DISRUPTION

V. A. Sharma

Department of Mathematics, Smt. Narsamma Arts, Commerce and Science college, Amravati 444606
DOI:https://doi.org/10.55041/ijcope.v2i8.196

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Abstract

Quantum computing offers transformative potential for addressing complex combinatorial optimization challenges in logistics and supply chain management. This paper presents a comprehensive investigation of quantum annealing and hybrid quantum-classical algorithms applied to unit load device (ULD) configuration and disruption management in air cargo and multimodal logistics networks. We formulate the ULD loading and placement problem as a Quadratic Unconstrained Binary Optimization (QUBO) model that incorporates weight, volume, center-of-gravity, structural stress, and compatibility constraints. A stratified hybrid architecture spanning physical quantum hardware, algorithmic middleware, and decision-support layers is proposed. Through extensive numerical experiments and comparison with classical solvers, we demonstrate superior payload utilization (up to 96.5%), favorable computational scaling, and rapid disruption recovery. Real-world industry pilots, including quantum-assisted route optimization achieving substantial carbon emission reductions and hybrid solutions at major ports, are analyzed. Results indicate that while noisy intermediate-scale quantum (NISQ) hardware limitations persist, hybrid approaches already deliver measurable gains in operational efficiency, cost reduction, and supply-chain resilience. The work provides a practical roadmap for near-term adoption of quantum technologies in high-stakes logistics environments.

Keywords— Quantum annealing, Unit load device (ULD), QUBO, Logistics optimization, Disruption management, Hybrid quantum-classical algorithms, Air cargo, Supply chain resilience

 

How to Cite this Paper

Sharma, V. A. (2026). Quantum Computing for Logistics Optimization: Annealing in ULD Configuration and Disruption. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(8), 1-9. https://doi.org/10.55041/ijcope.v2i8.196

Sharma, V.. "Quantum Computing for Logistics Optimization: Annealing in ULD Configuration and Disruption." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 8, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i8.196.

Sharma, V.. "Quantum Computing for Logistics Optimization: Annealing in ULD Configuration and Disruption." International Journal of Creative and Open Research in Engineering and Management 02, no. 8 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i8.196.

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References


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  • Akarshan Gulhane,“ Spectral Framework Based on the FKF Transform for Supply Chain Dynamics and Resilience,” International Journal of Creative and Open Research in Engineering and Management ISSN: 3108-1754 (Online) Volume 02 Issue 08 Augustl-2026, DOI:  https://doi.org/10.55041/ijcope.v2i8.140

  • Akarshan Gulhane,“ Spectral Differential Properties of the Distributional FKF Transform with Applications to Resilient Supply-Chain Systems,” International Journal of Creative and Open Research in Engineering and Management ISSN: 3108-1754 (Online) Volume 02 Issue 08 Augustl-2026, DOI:  https://doi.org/10.55041/ijcope.v2i8.139

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  • Akarshan Gulhane,“ The FKF Transform: Exponential Modulation Properties And Applications To Secure Digital Supply-Chain Networks,” International journal of Engineering sciences and Advanced Technology, Published:11-12-2025, Issue: Vol. 25 No. 12 (2025), Page Nos: 617 – 623, DOI: Https://doi.org/10.64771/ijesat.2025.v25.i12.3818

  • Akarshan Gulhane, “Spectral Differential Properties of the Distributional FKF Transform with Applications to Resilient Supply-Chain Systems,” International Journal of Creative and Open Research in Engineering and Management ISSN: 3108-1754 (Online) Volume 02 Issue 08 Augustl-2026, DOI: https://doi.org/10.55041/ijcope.v2i8.139.

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  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: Aug 24 2026
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