Multi-objective optimization for Work-In-Process balancing and throughput maximization in global fab scheduling

被引：0
|
作者：
Barhebwa-Mushamuka, F. [1 ]
Dauzere-Peres, S. [1 ]
Yugma, C. [1 ]
机构：
[1] Univ Clermont Auvergne, Mines St Etienne, CNRS, UMR 6158,LIMOS,CMP,Dept Mfg Sci & Logist, F-13541 Gardanne, France
来源：
2019 IEEE 15TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE) | 2019年
关键词：
D O I：
暂无
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 a multi-objective optimization approach for global fab scheduling, based on a mathematical model that determines production targets, i.e. product quantities to complete in each operation and each period on a scheduling horizon. The multi-objective approach balances product mix variability minimization and throughput maximization using an epsilon-constraint approach. For evaluation purposes, the global fab scheduling model is coupled with a generic multi-method simulation model. Numerical experiments conducted on industrial data illustrate the effectiveness of the approach.
引用
收藏
页码：697 / 702
页数：6
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