A Novel Hybrid Method for Solving Flexible Job-Shop Scheduling Problem
Tao Ning1, 2, Chen Guo2, *, Rong Chen2, Hua Jin1
1 College of Software, Dalian Jiaotong University, China
2 College of Information Science and Technology, Dalian Maritime University, China
Abstract
For the purpose of solving the flexible job-shop scheduling problem (FJSP), an improved quantum genetic algorithm based on earliness/tardiness penalty coefficient is proposed in this paper. For minimizing the completion time and the job-shop cost, a simulation model was established firstly. Next, according to the characteristics of the due in production, a double penalty coefficient was designed and a double chains coding method was proposed. At last, the effectiveness of the proposed method is verified through being applied to the Kacem example and compared with some existing algorithms.
Keywords: Double chains coding, flexible job-shop scheduling problem, penalty coefficient, quantum algorithm.
Article Information
Article History:
Received Date: 18/2/2015
Revision Received Date: 18/9/2015
Acceptance Date: 19/9/2015
Electronic publication date: 25/3/2016
Collection year: 2016
© Ning et al.; Licensee Bentham Open.
open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (
https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
* Address correspondence to this author at the College of Information Science and Technology, Dalian Maritime University, China; Tel/Fax: 8613940901029;
E-mail: daliannt1@126.com
Open Peer Review Details |
Manuscript submitted on 18-2-2015 |
Original Manuscript |
A Novel Hybrid Method for Solving Flexible Job-Shop Scheduling Problem |