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International Journal of Creative and Open Research in Engineering and Management

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Volume 02, Issue 8

Published on: August 2026

FORMULATIONS FOR QUANTUM ANNEALED PROJECT SCHEDULING

U Kanade

Dept of Mathematics/ GCOE Karad/India

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

Resource constrained project scheduling and related allocation tasks can be expressed as Quadratic Unconstrained Binary Optimization (QUBO) models and submitted to quantum annealers. This paper develops the QUBO formulation in detail: choice of binary variables, linear and quadratic objective terms, conversion of precedence and resource constraints into penalty functions, and calibration of penalty weights. The resulting Hamiltonian is embedded onto quantum hardware, annealed, and post-processed. Hybrid classical–quantum workflows that wrap the QUBO solver inside Monte Carlo risk analysis or a digital twin are examined. Supporting process flowcharts and energy-landscape figures illustrate every stage. The treatment remains grounded in construction and logistics applications while remaining transferable to other combinatorial domains such as ULD configuration.

Keywords: QUBO formulation; quantum annealing; Ising model; penalty methods; resource-constrained project scheduling; hybrid quantum-classical; minor embedding; Monte Carlo; digital twin.

How to Cite this Paper

Kanade, U. (2026). Formulations for Quantum Annealed Project Scheduling. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(8), 1-9. https://doi.org/10.55041/ijcope.v2i8.065

Kanade, U. "Formulations for Quantum Annealed Project Scheduling." 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.v2i8.065.

Kanade, U. "Formulations for Quantum Annealed Project Scheduling." 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.v2i8.065.

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  • Peer Review Type: Double-Blind Peer Review
  • Published on: Aug 22 2026
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