TY - JOUR
T1 - A NSGA-II based memetic algorithm for multiobjective parallel flowshop scheduling problem
AU - Wang, Hongfeng
AU - Fu, Yaping
AU - Huang, Min
AU - Huang, George Q.
AU - Wang, Junwei
N1 - Funding Information:
This work was supported by National Nature Science Foundation of China (NSFC) (Grant Nos. 71671032 , 71571156 , 61703220 , 71620107003 , 61621004 ) and by the Fundamental Research Funds for the Central Universities (Grant No. N160402002 ).
Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2017/11
Y1 - 2017/11
N2 - 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.
AB - 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.
KW - Memetic algorithm
KW - Multiobjective evolutionary computation
KW - Multiobjective scheduling
KW - Parallel flowshop scheduling
UR - http://www.scopus.com/inward/record.url?scp=85029545192&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2017.09.009
DO - 10.1016/j.cie.2017.09.009
M3 - Journal article
AN - SCOPUS:85029545192
SN - 0360-8352
VL - 113
SP - 185
EP - 194
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
ER -