华南理工大学学报(自然科学版) ›› 2008, Vol. 36 ›› Issue (9): 64-70.

• 计算机科学与技术 • 上一篇    下一篇

基于机会约束规划的ERP实施方案优化模型

王少君 王刚 吕民 高国安   

  1. 哈尔滨工业大学 机电工程学院, 黑龙江 哈尔滨 150001
  • 收稿日期:2007-07-24 修回日期:2007-12-20 出版日期:2008-09-25 发布日期:2008-09-25
  • 通信作者: 王少君(1971-),男,博士生,主要从事CIMS、企业信息化实施与评价、ERP决策支持系统研究. E-mail:wang_shao—jun@126.com
  • 作者简介:王少君(1971-),男,博士生,主要从事CIMS、企业信息化实施与评价、ERP决策支持系统研究.
  • 基金资助:

    国家“863”/CIMS主题资助项目(2003AA413210)

Optimization Models of ERP Implementation Project Based on Chance-Constrained Programming

Wang Shao-jun  Wang Gang  LU Min  Gao Guo-an   

  1. School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China
  • Received:2007-07-24 Revised:2007-12-20 Online:2008-09-25 Published:2008-09-25
  • Contact: 王少君(1971-),男,博士生,主要从事CIMS、企业信息化实施与评价、ERP决策支持系统研究. E-mail:wang_shao—jun@126.com
  • About author:王少君(1971-),男,博士生,主要从事CIMS、企业信息化实施与评价、ERP决策支持系统研究.
  • Supported by:

    国家“863”/CIMS主题资助项目(2003AA413210)

摘要: 为了解决企业ERP实施规划方案中的时间、成本、质量不确定优化问题。结合PERT技术提出了基于机会约束规划的实施进度、实施进度一费用和实施质量优化模型及进度一费用一质量联合折衷模型.采用随机模拟技术通过Monte Carlo仿真给出了项目实施风险的概率估计,并利用嵌入PERT的基于随机模拟的遗传算法对模型进行求解.最后通过算例验证了文中提出的模型的合理性和算法的有效性,为企业ERP实施方案的规划提供了可靠的方法.

关键词: 项目管理, 企业资源计划, 机会约束规划, 计划评审技术, 遗传算法

Abstract:

In order to solve the uncertain optimization problems of time, cost and quality existing in the project implementation process of enterprise resource planning (ERP), the program evaluation and review technique (PERT) is employed to establish the optimization models of the implementation schedule, the implementation schedule-cost tradeoff, the implementation quality and the implementation schedule-cost-quality tradeoff. Then, the risk probability of project implementation is estimated via the Monte Carlo simulation. Moreover, a PERT-embedded genetic algorithm based on the stochastic simulation technique is introduced to solve the proposed models. It is demonstrated by an example that the proposed models and algorithm are reasonable and effective, and are reliable for the programming of ERP project implementation.

Key words: project management, enterprise resource planning, chance-constrained programming, program evaluation and review technique, genetic algorithm