OPTIMIZING BI-CRITERIA PERMUTATION FLOW SHOP SCHEDULING PROBLEM BY IMPROVED NSGA III

被引:0
作者
Meng, Ronghua [1 ,2 ]
Rao, Yunqing [1 ]
Luo, Qiang [1 ]
机构
[1] Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan, Hubei, Peoples R China
[2] China Three Gorges Univ, Hubei Key Lab Hydroelect Machinery Design & Maint, Yichang, Hubei, Peoples R China
来源
PROCEEDINGS OF THE ASME 13TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2018, VOL 4 | 2018年
基金
中国国家自然科学基金;
关键词
flow shop scheduling problem; NSGA III; bi-objective problem; makespan; total tardiness; SEARCH ALGORITHM; MAKESPAN;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper addresses a bi-objective distribution permutation flow shop scheduling problem(FSP) with setup times aiming to minimize the makespan and the total tardiness. It is very difficult to obtain an optimal solution by using traditional approaches in reasonable computational time. This paper presents an appropriate non-dominated sorting Genetic Algorithm III based on the reference point. The NEH strategy is applied into the generation of the initial solution set. To validate the performance of the NEH strategy improved NSGA III (NNSGA III) on solution quality and diversity level, various test problems are carried out. Three algorithms, including NSGA II, NEH strategy improved NSGA II( NNSGA II) and NNSGA III are utilized to solve this FSP. Experimental results suggest that the proposed NNSGA III outperforms the other algorithms on the Inverse Generation Distance metric, and the distribution of Pareto solutions are improved excellently.
引用
收藏
页数:5
相关论文
共 14 条
[1]   Permutation flow shop scheduling with earliness and tardiness penalties [J].
Chandra, Pankaj ;
Mehta, Peeyush ;
Tirupati, Devanath .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2009, 47 (20) :5591-5610
[2]   A fast and elitist multiobjective genetic algorithm: NSGA-II [J].
Deb, K ;
Pratap, A ;
Agarwal, S ;
Meyarivan, T .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (02) :182-197
[3]   An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints [J].
Deb, Kalyanmoy ;
Jain, Himanshu .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2014, 18 (04) :577-601
[4]  
Garey M. R., 1976, Mathematics of Operations Research, V1, P117, DOI 10.1287/moor.1.2.117
[5]   An improved NSGA-II algorithm for multi-objective lot-streaming flow shop scheduling problem [J].
Han, Yu-Yan ;
Gong, Dun-wei ;
Sun, Xiao-Yan ;
Pan, Quan-Ke .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2014, 52 (08) :2211-2231
[6]   MINIMIZING THE MAKESPAN IN THE 3-MACHINE ASSEMBLY-TYPE FLOWSHOP SCHEDULING PROBLEM [J].
LEE, CY ;
CHENG, TCE ;
LIN, BMT .
MANAGEMENT SCIENCE, 1993, 39 (05) :616-625
[7]   Minimizing energy consumption and tardiness penalty for fuzzy flow shop scheduling with state-dependent setup time [J].
Liu, Guo-Sheng ;
Zhou, Ya ;
Yang, Hai-Dong .
JOURNAL OF CLEANER PRODUCTION, 2017, 147 :470-484
[8]   Hybrid monkey search algorithm for flow shop scheduling problem under makespan and total flow time [J].
Marichelvam, M. K. ;
Tosun, Omur ;
Geetha, M. .
APPLIED SOFT COMPUTING, 2017, 55 :82-92
[9]   A HEURISTIC ALGORITHM FOR THE M-MACHINE, N-JOB FLOWSHOP SEQUENCING PROBLEM [J].
NAWAZ, M ;
ENSCORE, EE ;
HAM, I .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 1983, 11 (01) :91-95
[10]   A local-best harmony search algorithm with dynamic sub-harmony memories for lot-streaming flow shop scheduling problem [J].
Pan, Quan-Ke ;
Suganthan, P. N. ;
Liang, J. J. ;
Tasgetiren, M. Fatih .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (04) :3252-3259