基于遗传算法的网络规划风险要素传递理论研究

Cunbin Li, Kecheng Wang
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引用次数: 5

摘要

项目风险管理是一般项目风险要素传递理论的一个重要方面。传统的网络规划技术在项目风险管理问题上遇到了很大的障碍,而且往往无法准确预测风险,造成很大的成本损失。为了解决考虑风险因素的成本-时间优化问题,本文建立了网络规划风险因素模型,将风险因素分为离散模型和连续模型分别进行讨论。在离散模型中引入成本和风险元素矩阵,得到相应的规划模型;在连续模型中,机器学习模型的思想被用来最小化期望的风险。在此模型的基础上,利用遗传算法高效快速的全局搜索能力,对Feng等人开发的遗传算法进行改进,增加风险元素,最终得到考虑风险元素的成本-时间曲线。这有效地解决了网络规划成本优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Research of Network Planning Risk Element Transmission Theory Based on Genetic Algorithm
Risk management project is an important aspect of general project risk element transmission theory. Traditional network planning technology encountered great obstacles in project risk management issues, and often unable to accurately forecast the risk, resulting great loss of costs. To address the cost-time optimization problem considering the risk elements, this paper established a network planning risk element model, which divides risk elements into discrete model and continuous model to be discussed separately. In the discrete model costs and risk element matrix is introduced to get the corresponding programming model; In Continuous model the idea of machine learning model is used to minimum the desired risk. Based on this model, by using genetic algorithm's efficient and rapid global search capability, this paper improves the genetic algorithm developed by Feng and others, increases the risk elements and eventually gets the cost-time curve considering risk elements. This effectively solves the network planning cost optimization problem.
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