Solving the resource constrained project scheduling problem with quantum annealing-Reference-Cited by-同舟云学术

Solving the resource constrained project scheduling problem with quantum annealing

Published:2024-07-22 Issue:1 Volume:14 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Pérez Armas Luis Fernando,Creemers Stefan,Deleplanque Samuel

Abstract

AbstractQuantum annealing emerges as a promising approach for tackling complex scheduling problems such as the resource-constrained project scheduling problem (RCPSP). This study represents the first application of quantum annealing to solve the RCPSP, analyzing 12 well-known mixed integer linear programming (MILP) formulations and converting the most qubit-efficient one into a quadratic unconstrained binary optimization (QUBO) model. We then solve this model using the D-wave advantage 6.3 quantum annealer, comparing its performance against classical computer solvers. Our results indicate significant potential, particularly for small to medium-sized instances. Further, we introduce time-to-target and Atos Q-score metrics to evaluate the effectiveness of quantum annealing and reverse quantum annealing. The paper also explores advanced quantum optimization techniques, such as customized anneal schedules, enhancing our understanding and application of quantum computing in operations research.

Publisher

Springer Science and Business Media LLC

Link

https://www.nature.com/articles/s41598-024-67168-6.pdf

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