¹School of Management, Dalian University of Technology, Dalian 116024,China
²Institute of Software, Dalian Jiaotong University, Dalian 116045,China

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Abstract—In order to solve the problem of flexible job-shop scheduling, this paper proposed a novel quantum genetic algorithm based on cloud model. Firstly, a simulation model was established aiming at minimizing the completion time, the penalty and the total cost. Secondly, the method of double chains structure coding including machine allocation chain and process chain was proposed. The crossover operator and mutation operator were obtained by the cloud model X condition generator because of its randomness and stable tendency. The non dominated sorting strategy was introduced to obtain more optimal solution. Finally, the novel method was applied to the Kacem example and a mechanical mould scheduling, the simulation results demonstrated that the proposed method can reduce the precocious probability and obtain more non dominated solutions comparing with the existing algorithms.

Index Terms—Flexible job-shop scheduling, Cloud model, Quantum genetic algorithm, Double chains structure coding

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Cite: Xiaobing Liu, Xuan Jiao, Tao Ning, Ming Huang, "An Effective Method to Solve Flexible Job-shop Scheduling Based on Cloud Model, " Journal of Software vol. 9, no. 11, pp. 2948-2954, 2014.