Multi-objective Ant Colony Optimization for Production Line Balance and Dynamic Complexity

被引:0
|
作者
Law, Edward Ko Wah [1 ]
Yung, Winco K. C. [1 ]
机构
[1] Hong Kong Polytech Univ, Dept Ind & Syst Engn, Hong Kong, Peoples R China
来源
2019 IEEE 4TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYSIS (ICCCBDA) | 2019年
关键词
mixed-model work flow; line balancing; information entropy; structural complexity; dynamic complexity; big data analytic; Matlab; SYSTEM;
D O I
10.1109/icccbda.2019.8725636
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The primary objective of this paper is to develop a mathematical framework to minimize the impact to the complexity of manufacturing systems in various configurations generated by line balance. The manufacturing systems are based on mixed model manufacturing where the same production stations can be used to produce various product models. Line balance has been studied in several decades and one of the objectives is to minimize the cycle time. It has been applied also to mixed mode manufacturing, and many researches end with a complex algorithm and line configuration that are inflexible and vulnerable to changes in the production situation. This paper is to show a mathematical framework that achieved a multi-objective Ant Colony Optimization for Production Line Balance and Dynamic Complexity with programming in MATLAB. It shows that the same heuristic search can be reinforced by both pheromones: 1. Line Balance, 2. Dynamic Complexity.
引用
收藏
页码:284 / 289
页数:6
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