A two phase optimization method for Petri net models of manufacturing systems
A two phase optimization method for Petri net models of manufacturing systems
复制标题
制造系统Petri网模型的两阶段优化方法
DOI：
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复制
发表时间：
2001
影响因子：
8.3
通讯作者：
M. Suárez
中科院分区：
文献类型：
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作者：
A. Zimmermann;D. Rodriguez;M. Suárez
优化是大型制造系统设计中的一个关键问题。首先需要一个适当的建模形式主义来表达竞争与合作关系的复杂交织。此外，强大而有效的优化技术是必要的。本文提出了一种集成工具的DEDS的自动优化，应用于制造系统。在对制造系统中的优化问题进行快速概述之后，介绍了两种现有的建模和评估工具与Petri网和基于模拟退火的通用优化包的集成。考虑高速缓存和两阶段优化技术允许将优化加速约35倍。在第一个预优化阶段，最佳参数集的粗略近似计算的基础上的性能界限。两个应用实例表明所提出的技术的好处。
Optimization is a key issue in the design of large manufacturing systems. An adequate modeling formalism to express the intricate interleaving of competition and cooperation relationships is needed first. Moreover, robust and efficient optimization techniques are necessary. This paper presents an integrated tool for the automated optimization of DEDS, with application to manufacturing systems. After a very quick overview of optimization problems in manufacturing systems, it presents the integration of two existing tools for the modeling and evaluation with Petri nets and a general-purpose optimization package based on simulated annealing. The consideration of a cache and a two phase technique for optimization allows to speed-up the optimization by a factor of about 35. During the first preoptimization phase, a rough approximation of the optimal parameter set is computed based on performance bounds. Two application examples show the benefits of the proposed technique.