Iterated Greedy Algorithms for Flow-Shop Scheduling Problems: A Tutorial

被引:89
作者
Zhao, ZiYan [1 ,2 ]
Zhou, MengChu [3 ,4 ,5 ]
Liu, ShiXin [1 ,2 ]
机构
[1] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
[2] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[3] New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA
[4] Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China
[5] Macau Univ Sci & Technol, Collaborat Lab Intelligent Sci & Syst, Macau 999078, Peoples R China
基金
中国国家自然科学基金;
关键词
Tutorials; Job shop scheduling; Search methods; Optimization; Linear programming; Heuristic algorithms; Greedy algorithms; Flow-shop scheduling problem (FSP); heuristic algorithm; iterated greedy algorithm (IGA); review; tutorial; TOTAL TARDINESS MINIMIZATION; BEE COLONY ALGORITHM; BIOGEOGRAPHY-BASED OPTIMIZATION; TOTAL WEIGHTED TARDINESS; DEPENDENT SETUP TIMES; PERMUTATION FLOWSHOP; MINIMIZING MAKESPAN; HYBRID FLOWSHOP; DIFFERENTIAL EVOLUTION; EFFICIENT HEURISTICS;
D O I
10.1109/TASE.2021.3062994
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An iterated greedy algorithm (IGA) is a simple and powerful heuristic algorithm. It is widely used to solve flow-shop scheduling problems (FSPs), an important branch of production scheduling problems. IGA was first developed to solve an FSP in 2007. Since then, various FSPs have been tackled by using IGA-based methods, including basic IGA, its variants, and hybrid algorithms with IGA integrated. Up until now, over 100 articles related to this field have been published. However, to the best of our knowledge, there is no existing tutorial or review paper of IGA. Thus, we focus on FSPs and provide a tutorial and comprehensive literature review of IGA-based methods. First, we introduce a framework of basic IGA and give an example to clearly show its procedure. To help researchers and engineers learn and apply IGA to their FSPs, we provide an open platform to collect and share related materials. Then, we make classifications of the solved FSPs according to their scheduling scenarios, objective functions, and constraints. Next, we classify and introduce the specific methods and strategies used in each phase of IGA for FSPs. Besides, we summarize IGA variants and hybrid algorithms with IGA integrated, respectively. Finally, we discuss the current IGA-based methods and already-solved FSP instances, as well as some important future research directions according to their deficiency and open issues.
引用
收藏
页码:1941 / 1959
页数:19
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