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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >A Quantum-inspired Iterated Greedy algorithm for permutation flowshops in a collaborative manufacturing environment
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A Quantum-inspired Iterated Greedy algorithm for permutation flowshops in a collaborative manufacturing environment

机译：用于协作制造环境中置换流水车间的量子启发式迭代贪婪算法

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摘要

In this study, an effective Quantum-inspired Iterated Greedy algorithm (QIG) is proposed for permutation flowshops, which is the foundation for solving the problems with uncertainties in a collaborative manufacturing environment. A hybrid representation is developed to construct a Q-job by combining a job with a Q-bit. Q-Job permutations represent solutions, which can be evaluated directly. Hence, no representative conversion is needed, and the efficiency is enhanced. Based on Particle Swarm Optimisation, a new rotation gate is investigated to dynamically update Q-bits, so that the perturbation strength is modified adaptively. Experimental results show that the proposed rotation gate is effective and QIG significantly outperforms other existing algorithms for the considered problem.
机译：在这项研究中，提出了一种有效的量子启发式迭代贪婪算法（QIG）用于置换流水车间，这是解决协作制造环境中不确定性问题的基础。通过将作业与Q位相结合，开发了一种混合表示形式来构造Q作业。 Q-Job置换表示解决方案，可以直接对其进行评估。因此，不需要代表性的转换，并且提高了效率。基于粒子群优化技术，研究了一种新的旋转门来动态更新Q位，从而自适应地修改了摄动强度。实验结果表明，对于所考虑的问题，所提出的旋转门是有效的，并且QIG明显优于其他现有算法。

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