Neuro-tabu search approach to scheduling in automotive manufacturing

被引：1
|
作者：
Bozejko, Wojciech [1 ]
Burduk, Anna [2 ]
Musial, Kamil [2 ]
Pempera, Jaroslaw [1 ]
机构：
[1] Wroclaw Univ Technol, Fac Elect, Dept Automat Mechatron & Control Syst, Janiszewskiego 11-17, PL-50372 Wroclaw, Poland
[2] Wroclaw Univ Technol, Fac Mech Engn, Ignacego Lukasiewicza 5, PL-50371 Wroclaw, Poland
来源：
NEUROCOMPUTING | 2021年 / 452卷
关键词：
Metaheuristic; Discrete optimization; Neural mechanism; FLOW-SHOP PROBLEM; OPTIMIZATION; DESIGN;
D O I：
10.1016/j.neucom.2020.01.121
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The work concerns a new problem of minimizing production time of a set of tasks on machines while limiting the availability of machine operators. The problem is taken from practice, from a company producing subassemblies for the automotive industry. A mathematical model of the problem is formulated, and for its solution a neuro-tabu algorithm is proposed, which is a variation of the tabu search algorithm with a neural mechanism replacing the tabu list: short-term memory. The efficiency of the algorithm constructed in this way is verified on test examples based on real data from the production process. @& nbsp;2020 Elsevier B.V. All rights reserved.
引用
收藏
页码：435 / 442
页数：8
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