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Quantum-inspired hybrid algorithm for integrated process planning and scheduling

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE 2018年第6期232卷 1105-1122页

作者： Liu, Mi Yi, Shuping Wen, Peihan Chongqing Univ Coll Mech Engn Shazheng St Chongqing 400044 Peoples R China

Process planning and job shop scheduling problems are the two classical but crucial activities in manufacturing system. With the approach of integrated process planning and scheduling, the two actual activities are combined to conduct operation selection and operation sequencing with the constraints of practical job shop status. In this article, a quantum-inspired hybrid algorithm with the objective of minimum makespan is proposed, aiming to solve integrated process planning and scheduling problems in dynamic manufacturing systems. A hybrid-coding representation is suggested, which is a three-layer structure in numerical representation and Q-bit representation adopted from quantum-inspired evolutionary algorithm. Based on the hybrid-coding representation, customized converting and repairing rules and methods are presented to generate feasible individuals. Q-gate rotation and group leader optimization algorithm are integrated systematically for the population evolution to accelerate the convergence speed of the proposed algorithm. In order to increase the diversity of population, a chaotic map called logistic map is introduced, bringing the stochastic initial individuals. Experiments show that the proposed hybrid algorithm can generate outstanding outcomes for integrated process planning and scheduling instances.

关键词： Integrated process planning and scheduling quantum-inspired evolutionary algorithm group leader optimization algorithm chaotic maps hybrid algorithm

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Disruption Management for Predictable New Job Arrivals in Cloud Manufacturing

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JOURNAL OF INTELLIGENT SYSTEMS 2017年第4期26卷 683-695页

作者： Liu, Mi Yi, Shuping Wen, Peihan Song, Haicao Chongqing Univ Coll Mech Engn Shazheng St Chongqing 400044 Peoples R China Shihezi Univ Coll Mech & Elect Engn Xinjiang 832003 Peoples R China

Manufacturing resources are shared and centrally managed on the cloud platform in cloud manufacturing, which is a new model of modern manufacturing. The production data are collected, which can be used to predict the manufacturing events. Based on those, disruption problems of scheduling should be researched from a new point of view. In this paper, new job arrivals were considered as the disruption event. The time of the occurrence of disruption was predictable in contrast to uncertainty. Alternative subcontractors chosen from the cloud platform were available for outsourcing with different processing prices and transporting distances. The objective of the original scheduling, the deviation between the new schedule and the old one, and the outsourcing cost were all considered. To express the problem, mathematical models and a three-field notation model were constructed. To solve the problem, a hybrid quantum-inspired chaotic group leader optimization algorithm was proposed, in which a hybrid encoding way was applied. To verify the algorithm, experiments were carried out. The results showed that the proposed algorithm performs well.

关键词： Cloud manufacturing disruption management quantum-inspired evolutionary algorithm group leader optimization algorithm outsourcing

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