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System Dynamics Applied to Operations and Policy Decisions

机译：系统动力学应用于运营和政策决策

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摘要

This paper reviews how concepts and techniques of system dynamics are being applied in new ways to analyse the operations and formation of artificial and societal systems and then to make decisions about them. The ideas and modelling methods to describe natural and technological systems are mostly reductionist (or 'bottom-up') and based on general scientific principles, with ad-hoc elements for any particular system. But very complex and large systems involving science, technology and society, whose complete descriptions and predictions are impossible, can still be designed, controlled and managed using the methods of system dynamics, where they are focused on the outputs of the system in relation to the input data available, and relevant external influences. For many complex systems with uncertain behaviour, their models typically combine concepts and methods of bottom-up system dynamics with statistical modelling of past or analogous data and optimization of outputs. System dynamics that has been generalized by advances in mathematical, scientific and technological research over the past 50 years, together with new approaches to the use of data and ICT, has led to powerful qualitative verbal and schematic concepts as well as improved quantitative methods, both of which have been shown to be of great assistance to decisions, notably about different types of uncertainty and erratic behaviour. This approach complements traditional decision-making methods, by introducing greater clarity about the process, as well as providing new techniques and general concepts for initial analysis, system description - using data in non-traditional ways - and finally analysis and prediction of the outcomes, especially in critical situations where system behaviour cannot be analysed by traditional decision-making methods. The scientific and international acceptance of system methods can make decision-making less implicit, and with fewer cultural assumptions. Topical examples of systems and decision-making are given.
机译：本文回顾了如何以新的方式应用系统动力学的概念和技术来分析人工和社会系统的运行和形成，然后做出决策。描述自然和技术系统的思想和建模方法大多是还原论（或“自下而上”）的，并基于一般的科学原理，对任何特定系统都有特定的要素。但是，涉及科学，技术和社会的非常复杂和大型的系统，不可能进行完整的描述和预测，仍然可以使用系统动力学的方法来设计，控制和管理，它们专注于与系统相关的系统输出。可用的输入数据以及相关的外部影响。对于许多行为不确定的复杂系统，其模型通常将自下而上的系统动力学的概念和方法与过去或类似数据的统计建模以及输出的优化相结合。在过去的50年中，数学，科学和技术研究的进步为系统动力学提供了广阔的发展空间，再加上使用数据和ICT的新方法，带来了强有力的定性语言和图解概念以及改进的定量方法，事实表明，其中有很大的帮助决策，尤其是关于各种类型的不确定性和行为不稳定的决策。这种方法通过使过程更加清晰明了，并为初始分析，系统描述（以非传统方式使用数据）以及最终对结果进行分析和预测提供了新技术和一般概念，从而对传统决策方法进行了补充，特别是在无法通过传统决策方法分析系统行为的紧急情况下。系统方法的科学和国际认可可以减少决策的隐性和文化假设。给出了系统和决策的典型例子。

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  • 来源
    《European review》 |2012年第3期|324-342|共19页
  • 作者

    J.C.R. HUNT; Y. TIMO SHKINA; P. J. B AUD AINS; S.R. BISHOP;

  • 作者单位

    Department of Earth Sciences, University College London, Gower Street, London, WCIE 6BT, UK,Department of Mathematics, University College London, Gower Street, London, WC1E 6BT, UK;

    Department of Mathematics, University College London, Gower Street, London, WC1E 6BT, UK;

    Department of Mathematics, University College London, Gower Street, London, WC1E 6BT, UK;

    Department of Mathematics, University College London, Gower Street, London, WC1E 6BT, UK;

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