Volume 9 Number 11 (Nov. 2014)
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JSW 2014 Vol.9(11): 2948-2954 ISSN: 1796-217X
doi: 10.4304/jsw.9.11.2948-2954

An Effective Method to Solve Flexible Job-shop Scheduling Based on Cloud Model

Xiaobing Liu1, Xuan Jiao1, Tao Ning2, Ming Huang2
1School of Management, Dalian University of Technology, Dalian 116024,China
2Institute of Software, Dalian Jiaotong University, Dalian 116045,China

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


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.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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