Solving Flexible Job-Shop Scheduling Problems Based on Quantum Computing

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Bibliografiset tiedot
Julkaisussa:	Entropy vol. 27, no. 2 (2025), p. 189
Päätekijä:	Fu, Kaihan
Muut tekijät:	Liu, Jianjun, Chen, Miao, Zhang, Huiying
Julkaistu:	MDPI AG
Aiheet:	Scheduling Quantum computing Integer programming Computers Mathematical models Combinatorial analysis Optimization Flexibility Variables Manufacturers Ising model Linear programming Manufacturing Feedback Energy consumption Job shop scheduling
Linkit:	Citation/Abstract Full Text + Graphics Full Text - PDF
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Kuvaus
Abstrakti:	Flexible job-shop scheduling problems (FJSPs) represent one of the most complex combinatorial optimization challenges. Modern production systems and control processes demand rapid decision-making in scheduling. To address this challenge, we propose a quantum computing approach for solving FJSPs. We propose a quadratic unconstrained binary optimization (QUBO) model to minimize the makespan of FJSPs, with the scheduling scheme encoded in the ground state of the Hamiltonian operator. The model is solved using a coherent Ising machine (CIM). Numerical experiments are conducted to evaluate and validate the performance and effectiveness of the CIM. The results demonstrate that quantum computing holds significant potential for solving FJSPs more efficiently than traditional computational methods.
ISSN:	1099-4300
DOI:	10.3390/e27020189
Lähde:	Engineering Database