硕士论文IT企业多项目进度管理和资源优化
上海交通大学
硕士学位论文
IT企业多项目进度管理和资源优化
姓名:樊仕君
申请
关于撤销行政处分的申请关于工程延期监理费的申请报告关于减免管理费的申请关于减租申请书的范文关于解除警告处分的申请
学位级别:硕士
专业:IT项目管理
指导教师:曹健
20090201
上海交通大学工程硕士学位论文
IT 企业多项目进度管理和资源优化
摘 要
进入 21 世纪后,全球生活环境和经济环境产生了巨大变化。与此相
适应,现代企业的生存环境也不同以往,企业中再也不是靠单一的产品或
服务维持生存,而是依赖多个项目的组合管理,进而内部的管理变革随之
产生。在管理工作中,企业单位一直关注的是建立和提升自身的核心竞争
力,这也是企业单位永恒的一个话题。可以说,企业的核心竞争力是企业
发展的引擎,是引领企业在激烈竞争中不断发展、前进的动力。
多项目管理的产生和需求原因来自多方面,既是企业内部环境转变的
结果,也是企业外部因素所致。这些因素将集中
表
关于同志近三年现实表现材料材料类招标技术评分表图表与交易pdf视力表打印pdf用图表说话 pdf
现在企业分工与组织的
变化、开发技术的变化、技术和管理的创新等方面。由于 IT 企业多是以
软硬件开发和系统集成以及后期的系统维护作为主要生存手段。IT 企业和
一般企业相比,有其自身优势但受技术更新程度、IT 项目特殊化和其资源
的限制,往往使得这些因素给多项目管理的实施带来更突出的影响。
IT 企业的核心竞争力是
人力资源
卫生院人力资源管理制度人力资源管理咨询——主要流程人力资源管理课程教学大纲某公司人力资源分析报告护理人力资源调配方案及措施
,如何用有限的资源分配到多项目
中,才能使 IT 企业的利益最大化,完成的时间最短,花费的成本最低,
这些都是本文所要探讨和解决的问题。
本文首先从 IT 企业的人力资源库评价和多项目优先级指标考量出
发,对企业中的人力资源和多项目划分优先级,运用 AHP 层次分析法和平
衡计分卡作为基础工具,并在此基础上作优化和调整,使结果更加合理可
行。
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上海交通大学工程硕士学位论文
IT 企业多项目进度管理和资源优化
在静态分析的基础上,本文运用遗传算法对资源进行优化配置,采用
项目延期时间最短与延期造成的总损失最小的多目标期望模型进行数学建
模。在多项目进度管理中到达一个阶段后,用遗传算法进行资源再调度,
做到多项目进度跟踪与资源协调。
最后在本文作者曾经参与过的项目组中挑选了三个有代表性的项目,
建立了优化模型,经用遗传算法进行优化后,比较了优化前后的数据,验
证了此算法的有效性。
关键词:多项目,优先级,遗传算法
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上海交通大学工程硕士学位论文
IT 企业多项目进度管理和资源优化
ABSTRACT
It is known that people’s living environment and economic environment
has been changed dramatically in the 21st century. Similarly, the environment of
modern enterprise is different from the past, which no longer just relies on
single products or services to compete with others, but to rely on a number of
projects in portfolio management. Consequently, the internal management of the
resulting also has been changed. The enterprise has always put sustained
attention to the establishment and upgrade of the core competence during the
course of management; this is a eternal topic of the enterprise. It can be said that
the core competence of enterprises is the engine of continuous development
and the power of advancement in the fierce competition.
The emergence of Multi-project management has many reasons: first, it is
the consequence of the internal changes in the enterprise’s environment; second,
it is the consequence of many external factors, which focus on the performance
of the enterprise division of labor organizations, the changes in the development
of the technology changes, technology and innovation management, and so on.
It is know that the IT business all but see the hardware and software
development, systems integration, and the latter part of the system maintenance
as a major means of survival. Compared to general enterprises, IT enterprises
have their own advantages. However, they are also restricted by the level of
technology updates, the specialization of IT projects and its resource. These
factors lead to more implementation of the project management more
prominent.
Human resources are the core competence in IT enterprises. How to
allocate limited resources to more projects in order to enable IT companies to
imize the interest of completing the shortest period of time, the cost of the
lowest cost? The article is to discuss and resolve the issue.
First of all, the article talk about the IT enterprise human resource base and
multi-project evaluation of the priority targets considerations, the enterprise of
human resources and division of priority projects, the use of AHP and BSC as a
tool for the foundation. And on that basis make the adjustment and optimization,
so that the results are more reasonable and feasible.
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上海交通大学工程硕士学位论文
IT 企业多项目进度管理和资源优化
On the basis of the static analysis, the article use the genetic algorithm to
optimize resource allocation, and construct the mathematical model accoding to
multi-objective expectancy model of the shortest delay time and the smallest
total losses led by project extension. After achieving a milestone in the multi-
project processing management, genetic algorithms are used to re-schedule
resource to track the progress of the project and the coordination of resources.
Finally, the author select three representative projects in the project team
that he had taken part in. After Optimized model, it is indeed proved to be
effective by compared data.
KEY WORDS :Multi-Project ,priority ,genetic algorithm