重大工程复杂性马尔科夫链—熵度量模型构建

Markov chain-entropy measurement model for measuring complexity of mage projects

摘要:

本文利用马尔科夫链来理解重大工程的不确定性和动态演化特征，利用熵理论来量化重大工程的复杂性水平，建立了重大工程复杂性的马尔科夫链-熵度量模型。结果表明，重大工程的复杂性包括技术、环境、组织、目标、信息和任务六个维度，并具有结构性、不确定性和动态性特征。马尔科夫链可以用来描述过程，熵可以用来量化复杂性。该研究可以揭示重大工程的宏观状态与微观状态之间的关系，测度重大工程的复杂性水平，分析可持续发展趋势并进行预测决策和控制。

Abstract:

In this paper, Markov chain is used to understand the uncertainty and dynamic evolution characteristics of major projects, and entropy theory is used to quantify the level of complexity of major projects, and a Markov chain-entropy measurement model of the complexity of major projects is established. The results show that the complexity of mega projects includes six dimensions of technology, environment, organization, goal, information and task, and has the characteristics of structure, uncertainty and dynamic. Markov chains can be used to describe processes and entropy can be used to quantify complexity. This research can reveal the relationship between the macro-state and micro-state of major projects, measure the complexity level of mega projects, analyze sustainable development trends, and conduct predictive decision-making and control.