Fuzzy job-shop scheduling problems: A review

被引：72

作者：

Abdullah, Salwani ^{[1
]}

Abdolrazzagh-Nezhad, Majid ^{[1
,2
]}

机构：

[1] Univ Kebangsaan Malaysia, Ctr Artificial Intelligence Technol, Data Min & Optimizat Res Grp, Bangi 43600, Selangor, Malaysia

[2] Univ Birjand, Dept Comp & Software Engn, Birjand, Iran

来源：

INFORMATION SCIENCES | 2014年 / 278卷

关键词：

Fuzzy job-shop scheduling; Review; Meta-heuristic algorithm; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; DISPATCHING RULES; PROCESSING TIME; TABU SEARCH; TARDINESS; DATES; PSO;

D O I：

10.1016/j.ins.2014.03.060

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Fuzzy job-shop scheduling problems (Fuzzy JSSPs) are a class of combinational optimization problems known as non-deterministic polynomial-hard problems. In recent decades, a number of researchers have expanded the theoretical models of Fuzzy JSSPs and introduced algorithms to solve them. This paper reviews the classification of Fuzzy JSSPs, constraints and objectives investigated in Fuzzy JSSPs, and the methodologies applied in solving Fuzzy JSSPs. The paper centers on reviewing meta-heuristic algorithms as state-of-the-art algorithms proposed for Fuzzy JSSPs. These algorithms are analyzed in three steps, namely, pre-processing, initialization procedures, and improvement algorithms. Finally, possible suggestions for future studies are obtained from this survey. (C) 2014 Elsevier Inc. All rights reserved.

引用

页码：380 / 407

页数：28

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