研究项目调度的模糊GERT新方法

M. Gavareshki
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引用次数: 19

摘要

本工作的目的是提出一种适用于科研项目调度的新技术。研究项目具有不同于其他项目的特殊特征。这些因素包括活动的定义、顺序和持续时间的不确定性;不确定的结果;有循环和循环的;并且没有重复的活动,因此需要特殊的工具和技术来安排这些项目。传统的调度技术不能模拟研究项目或有很多错误。模糊GERT网络利用GERT和模糊的功能,是伊朗研究项目调度的强大工具。本文提出了一种求解模糊GERT网络的新方法。在该方法中,活动持续时间和循环梯形模糊数表示重复次数,网络节点输出的活动属于一个模糊集。在该方法中,GERT网络的第一次计算是基于评估节点的。过程输出是计划网络和项目模糊完成时间。这些输出是模糊数,可以通过/spl alpha/ cuts进行分析。与现有的模糊GERT和概率GERT方法相比,该方法具有更强的适用性和更少的计算量。此外,该方法易于计算机化和更新。该方法也可用于科研项目的成本估算。为了验证,我们将该方法与存在模糊和概率GERT方法进行了比较,结果非常接近。我们还将其应用于一个电子学院。其结果比传统的CPM方法更为真实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New fuzzy GERT method for research projects scheduling
The aim of This work is to present a new applicable and suitable technique for research projects scheduling. Research projects have special characteristics that separate them from other projects. These include uncertainty in definition, sequence and duration time of activities; uncertain results; having loops and cycles; and no repetitive activities, so there is a need for special tools and techniques for scheduling these projects. Conventional scheduling techniques are not able to model research projects or have a lot of errors. Fuzzy GERT networks using capabilities of GERT and fuzzy, is powerful tools for scheduling, Iran research projects. This work presents a new method for solving fuzzy GERT networks. In this method, activity duration time and loops trapezoidal fuzzy numbers states repetition number, and output activities from nodes of network belong to a fuzzy set. In this method, the First time GERT networks computations are done based on evaluating nodes. Process outputs are scheduled network and project fuzzy completion time. These outputs are fuzzy numbers and can be analyzed by /spl alpha/ cuts. This method is more applicable and needs less computation than existing fuzzy and probability GERT methods. Besides, this method can get computerized and up to date easily. This method can be also applied for cost estimations in research projects. For checking validation, we compared this method with existence fuzzy and probability GERT methods, the results were very near to each other. We also applied it in an electronic institute. The results were more realistic than the results of their pervious method (CPM).
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