A NSGA-II based memetic algorithm for multiobjective parallel flowshop scheduling problem. (November 2017)
- Record Type:
- Journal Article
- Title:
- A NSGA-II based memetic algorithm for multiobjective parallel flowshop scheduling problem. (November 2017)
- Main Title:
- A NSGA-II based memetic algorithm for multiobjective parallel flowshop scheduling problem
- Authors:
- Wang, Hongfeng
Fu, Yaping
Huang, Min
Huang, George Q.
Wang, Junwei - Abstract:
- Highlights: Investigate a parallel non-identical flowshop scheduling problem. Develop a multiobjecitve model considering efficiency and cost criteria. Propose a novel NSGA-II based memetic algorithm to solve the model. Proposed algorithm outperforms two popular multiobjective EAs significantly. Abstract: In many real-world manufacturing applications, a number of parallel flowshops are often used to process the jobs. The scheduling problem in this parallel flowshop system has gained an increasing concern from the operational research community; however, multiple scheduling criteria are rarely considered simultaneously in the literature. In this paper, a special parallel flowshop scheduling (PFSS) problem that consists of two parallel non-identical shops, one with two consecutive machines and the other with only one machine, is investigated with two objective functions of minimizing the total flow time of jobs and the number of tardy jobs in the two-machine flowshop. A multiobjective evolutionary algorithm (MOEA) based memetic algorithm hybridizing the local search technique into the framework of NSGA-II, which is well known as the most popular MOEA, is proposed for addressing the investigated PFSS problem. A set of test instances are employed to examine the performance of the proposed algorithm in comparison with two peer MOEAs, which also adopt the similar algorithm mechanism of NSGA-II. Experimental results indicate the effectiveness and efficiency of the proposed NSGA-IIHighlights: Investigate a parallel non-identical flowshop scheduling problem. Develop a multiobjecitve model considering efficiency and cost criteria. Propose a novel NSGA-II based memetic algorithm to solve the model. Proposed algorithm outperforms two popular multiobjective EAs significantly. Abstract: In many real-world manufacturing applications, a number of parallel flowshops are often used to process the jobs. The scheduling problem in this parallel flowshop system has gained an increasing concern from the operational research community; however, multiple scheduling criteria are rarely considered simultaneously in the literature. In this paper, a special parallel flowshop scheduling (PFSS) problem that consists of two parallel non-identical shops, one with two consecutive machines and the other with only one machine, is investigated with two objective functions of minimizing the total flow time of jobs and the number of tardy jobs in the two-machine flowshop. A multiobjective evolutionary algorithm (MOEA) based memetic algorithm hybridizing the local search technique into the framework of NSGA-II, which is well known as the most popular MOEA, is proposed for addressing the investigated PFSS problem. A set of test instances are employed to examine the performance of the proposed algorithm in comparison with two peer MOEAs, which also adopt the similar algorithm mechanism of NSGA-II. Experimental results indicate the effectiveness and efficiency of the proposed NSGA-II based memetic algorithm in solving the multiobjective PFSS problem. … (more)
- Is Part Of:
- Computers & industrial engineering. Volume 113(2017)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 113(2017)
- Issue Display:
- Volume 113, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 113
- Issue:
- 2017
- Issue Sort Value:
- 2017-0113-2017-0000
- Page Start:
- 185
- Page End:
- 194
- Publication Date:
- 2017-11
- Subjects:
- Parallel flowshop scheduling -- Multiobjective scheduling -- Multiobjective evolutionary computation -- Memetic algorithm
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2017.09.009 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 5319.xml