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

页码：435 / 442

页数：8

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