作业车间调度
计算机科学
调度(生产过程)
蚁群优化算法
流水车间调度
分布式计算
数学优化
地铁列车时刻表
蚁群
工厂(面向对象编程)
工作车间
作业调度程序
运筹学
工业工程
人工智能
云计算
工程类
数学
操作系统
程序设计语言
作者
Imen Chaouch,Olfa Belkahla Driss,Khaled Ghèdira
标识
DOI:10.1007/978-3-319-60042-0_12
摘要
In this paper, we are interested in industrial plants geographically distributed and more precisely the Distributed Job shop Scheduling Problem (DJSP) in multi-factory environment. The problem consists of finding an effective way to assign jobs to factories then, to generate a good operation schedule. To do this, a bio-inspired algorithm is applied, namely the Elitist Ant System (EAS) aiming to minimize the makespan. Several numerical experiments are conducted to evaluate the performance of our algorithm applied to the Distributed Job shop Scheduling Problem and the results show the shortcoming of the Elitist Ant System compared to developed algorithms in the literature.
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