• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2011, Vol. 33 ›› Issue (12): 184-188.

• 论文 • 上一篇    下一篇

虚拟样机工程中的项目资源均衡优化研究

田丰春,杨种学,杨〓宁   

  1. (南京晓庄学院数学与信息技术学院,江苏 南京 211171)
  • 收稿日期:2010-06-07 修回日期:2010-10-20 出版日期:2011-12-24 发布日期:2011-12-25

Virtual Prototyping Engineering Project Resource Optimization

TIAN Fengchun,YANG Zhongxue,YANG Ning   

  1. (School of Mathematics and Information Technology,Nanjing Xiaozhuang College,Nanjing 210017,China)
  • Received:2010-06-07 Revised:2010-10-20 Online:2011-12-24 Published:2011-12-25

摘要:

虚拟样机工程的复杂性不断增加,需有科学的项目管理技术来实现高效组织与管理。在工程项目资源均衡优化的调整中,通常以资源方差来衡量资源的均衡性,方差越小资源均衡性就越好,但其调整过程通常要经过一系列繁琐的推断过程。本文引入遗传算法,针对其中的“工期固定—资源均衡”问题,同时考虑作业之间的相关性限制约束,建立模型并求解;在多种资源优化中,根据每种资源对其资源均衡程度的重要性,给定权系数,用多目标优化中的线性加权系数法,将多种资源优化问题转化为按单种资源优化方法来求解,有效地解决了虚拟样机工程中的项目资源均衡优化问题。

关键词: 虚拟样机工程, 项目管理, 资源优化, 遗传算法

Abstract:

As virtual prototype becomes increasingly sophisticated, scientific techniques of project management will be needed to obtain efficient organization and management. While adjusting the resource balance and optimization of the project, resource variance is usually used to measure whether the resources are balanced or not, that is, the smaller the resource variance is, the more balanced the resources are, but the adjustment process usually goes through a series of tedious inference procedure. In this case, this essay, taking the advantage of GA, focuses on the problem of “regular project period, balanced resource”, and meanwhile takes into account the mutual restriction among the relevant performances; dealing with optimization in a variety of resources, the essay suggests that a  fixed weight should be given according to the importance of each resource in the balanced degree of resources, and with the linear weighting method in multiobjective optimization, the multiresource optimization problem is transformed into a single resource optimization,so that the resource optimization in a virtual prototype can be achieved eventually.

Key words: virtual prototyping engineering;project management;resource optimization;GA