• 论文 •    

多项目环境下经营过程配置优化

周永华,陈禹六   

  1. 清华大学自动化系,北京100084
  • 出版日期:2003-06-15 发布日期:2003-06-25

Optimization of Business Process Assignment in Multi-project Environment

ZHOU Yong - hua, CHEN Yu - liu   

  1. Dep. of Automation, Tsinghua Univ., Beijing100084, China
  • Online:2003-06-15 Published:2003-06-25

摘要: 在多项目环境下,根据供应链节点经营性能的变化,迅速合理地配置企业内和企业外资源的能力,是企业敏捷性评价的一个重要指标。阐述了项目的定义,从一般意义上给出了项目计划的参考模型。在经营过程中,存在许多决策节点,给出了扩展的AON图,结构化描述带有决策节点的经营过程。建立了折衷考虑资源、时间和成本约束,以及决策节点的多项目环境下的经营过程配置优化解析模型。应用遗传算法处理随机资源分配,并通过有限次遗 传操作逐步逼近全局最优解;应用栈技术和统一的时间窗处理多项目环境下资源冲突,以及经营过程中的决策节点,进行虚拟的活动安排,从而计算多个项目的完成时间和成本,最终使得配置优化和决策优化同步进行。本文提出的经营过程配置优化方法,可以扩展至围绕企业间共同项目和各自不同项目的分布式自主优化,给权益相关者带来价值增值。

关键词: 多项目, 经营过程计划, 配置优化, 决策优化, 遗传算法

Abstract: In multi-project environment, it is a significant indicator of agility evaluation to promptly and rationally assign the resources of intra- & extra-enterprise according to the changes of business performances of nodes in the supply chain. The definition of project is elaborated, and the reference model of project planning is given in generalized meaning. The extended AON (Activity on Node) graph is utilized to structurize the business process with decision nodes. The analytic model of business process assignment optimization is presented to undertake the trade-off among resource, time, cost constraints and decision nodes in multi-project environment. The genetic algorithm is employed to tackle the random allocation of resources and to achieve the global optimal solution through limited genetic operators, then the stack technique and the unified time window are used to deal with resource conflicts and decision nodes so as to undertake virtual arrangement of activities and compute the completion time and costs of multiple projects. Based on these, the assignment and decision optimization can be synchronously managed. The approach of business process assignment optimization presented in this paper can be extended to the application of bringing added value to all the stakeholders through the distributed independent optimization centering around the common project and respective various projects of inter-enterprises.

Key words: multiple projects, business process planning, assignment optimization, decision optimization, genetic algorithm

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