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A Quality Forecasting System For Glass Melting Processes Using Genetic Algorithms 基于遗传算法的玻璃熔制过程质量预测系统
发布日期: 2000-11-01
为了应对当今频繁变化的复杂业务流程,利用CIMOSA行为规则和自由选择Petri网,提出了一种结构化的制造企业业务流程建模算法。行为良好的属性(如活跃性和有界性)对企业业务流程至关重要。它们可以避免流程模型中可能出现的死锁、无休止的循环和悬而未决的任务。然而,对于复杂系统来说,良好性能的检查是一个NP难问题。本文提出了一种结构化过程建模算法。该算法得到的过程模型是自由选择Petri网,其良好的性能可以在多项式时间内确定。该算法生成的过程模型还具有模块化、可读性和可维护性的优点。
To deal with today's frequently changing and complex business processes, this paper presents a structured modeling algorithm for manufacturing enterprise business processes by using CIMOSA behavioral rules and free-choice Petri nets. The well-behaved properties such as liveness and boundedness are critical for enterprise business processes. They enable the avoidance of possible deadlock, endless loops and dangling tasks in process models. However, for complex systems, the checking of the well-behaved property is a NP-hard problem. In this paper, a structured process modeling algorithm is presented. The resulting process models from this algorithm are free-choice Petri nets whose well-behaved property can be decided in polynomial time. The process models resulted from this algorithm also have the advantages of modularity, readability, and maintainability.
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发布单位或类别: 日本-日本船用装置工业会
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