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Solving Flexible Job-Shop Scheduling Problems Based on Quantum Computing.

Kaihan Fu1, Jianjun Liu1, Miao Chen1

  • 1College of Science, China University of Petroleum, Beijing 102249, China.

Entropy (Basel, Switzerland)
|February 26, 2025
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Summary
This summary is machine-generated.

Quantum computing offers a novel solution for complex flexible job-shop scheduling problems (FJSPs). This approach uses a quantum model solved by a coherent Ising machine, showing potential for faster scheduling than traditional methods.

Keywords:
coherent Ising machineflexible job-shop scheduling problemquadratic unconstrained binary optimizationquantum computing

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Area of Science:

  • Operations Research
  • Quantum Computing
  • Computational Optimization

Background:

  • Flexible job-shop scheduling problems (FJSPs) are complex combinatorial optimization challenges.
  • Rapid decision-making is crucial for modern production and control systems.
  • Existing computational methods face limitations in solving large-scale FJSPs efficiently.

Purpose of the Study:

  • To propose a quantum computing approach for solving FJSPs.
  • To develop a Quadratic Unconstrained Binary Optimization (QUBO) model for FJSP makespan minimization.
  • To leverage a Coherent Ising Machine (CIM) for solving the proposed QUBO model.

Main Methods:

  • Formulation of an FJSP model using QUBO.
  • Encoding the scheduling scheme into the ground state of a Hamiltonian operator.
  • Solving the QUBO model on a Coherent Ising Machine (CIM).
  • Conducting numerical experiments to validate the CIM's performance.

Main Results:

  • The CIM effectively solved the QUBO formulation of FJSPs.
  • Numerical experiments demonstrated the feasibility and effectiveness of the quantum approach.
  • The quantum computing method showed potential for improved efficiency compared to classical methods.

Conclusions:

  • Quantum computing, specifically using CIMs, presents a promising avenue for addressing complex FJSPs.
  • The proposed QUBO model and CIM solution offer a potential pathway to more efficient scheduling.
  • Further research and development in quantum algorithms could significantly enhance production scheduling capabilities.