Multiobjective memetic algorithms for time and space assembly line balancing

被引：27
作者：
Chica, Manuel [1 ]
Cordon, Oscar [1 ,2 ]
Damas, Sergio [1 ]
Bautista, Joaquin [3 ]
机构：
[1] European Ctr Soft Comp, Mieres 33600, Spain
[2] ETS Informat & Telecomunicac, Dept Comp Sci & Artificial Intelligence, Granada 18071, Spain
[3] Univ Politecn Cataluna, Nissan Chair ETSEIB, E-08028 Barcelona, Spain
来源：
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2012年 / 25卷 / 02期
关键词：
Time and space assembly line balancing problem; Automotive industry; Multiobjective optimisation; Memetic algorithms; NSGA-II; Ant colony optimisation; GRASP; Local search; LOCAL SEARCH; EVOLUTIONARY ALGORITHMS; GENETIC ALGORITHM; 1/3; VARIANT; DESIGN;
D O I：
10.1016/j.engappai.2011.05.001
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents three proposals of multiobjective memetic algorithms to solve a more realistic extension of a classical industrial problem: time and space assembly line balancing. These three proposals are, respectively, based on evolutionary computation, ant colony optimisation, and greedy randomised search procedure. Different variants of these memetic algorithms have been developed and compared in order to determine the most suitable intensification-diversification trade-off for the memetic search process. Once a preliminary study on nine well-known problem instances is accomplished with a very good performance, the proposed memetic algorithms are applied considering real-world data from a Nissan plant in Barcelona (Spain). Outstanding approximations to the pseudo-optimal non-dominated solution set were achieved for this industrial case study. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码：254 / 273
页数：20
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