The complexity of issues requiring rational decision making grows and thus such decisions are becoming more and more difficult, despite advances in methodology and tools for decision support and in other areas of research. Globalization, interlinks between environmental, industrial, social and political issues, and rapid speed of change all contribute to the increase of this complexity. Specialized knowledge about decision-making processes and their support is increasing, but a large spectrum of approaches presented in the literature is typically illustrated only by simple examples. Moreover, the integration of model-based decision support methodologies and tools with specialized model-based knowledge developed for handling real problems in environmental, engineering, industrial, economical, social and political activities is often not satisfactory. Therefore, there is a need to present the state of art of methodology and tools for development of model-based decision support systems, and illustrate this state by applications to various complex real-world decision problems. The monograph reports many years of experience of many researchers, who have not only contributed to the developments in operations research but also succeeded to integrate knowledge and craft of various disciplines into several modern decision support systems which have been applied to actual complex decision-making processes in various fields of policy making. The experience presented in this book will be of value to researchers and practitioners in various fields. The issues discussed in this book gain in importance with the development of the new era of the information society, where information, knowledge, and ways of processing them become a decisive part of human activities. The examples presented in this book illustrate how how various methods and tools of model-based decision support can actually be used for helping modern decision makers that face complex problems. Overview of the contents: The first part of this three-part book presents the methodological background and characteristics of modern decision-making environment, and the value of model-based decision support thus addressing current challenges of decision support. It also provides the methodology of building and analyzing mathematical models that represent underlying physical and economic processes, and that are useful for modern decision makers at various stages of decision making. These methods support not only the analysis of Pareto-efficient solutions that correspond best to decision maker preferences but also allow the use of other modeling concepts like soft constraints, soft simulation, or inverse simulation. The second part describes various types of tools that are used for the development of decision support systems. These include tools for modeling, simulation, optimization, tools supporting choice and user interfaces. The described tools are both standard, commercially available, and nonstandard, public domain or shareware software, which are robust enough to be used also for complex applications. All four environmental applications (regional water quality management, land use planning, cost-effective policies aimed at improving the European air quality, energy planning with environmental implications) presented in the third part of the book rely on many years of cooperation between the authors of the book with several IIASA's projects, and with many researchers from the wide IIASA network of
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这本书的书名就足以吸引我,"Model-Based Decision Support Methodology with Environmental Applications (Mathematical Modelling)",光是“模型驱动的决策支持方法”和“环境应用”这两个关键词,就勾起了我对如何将严谨的数学建模应用于解决现实世界环境问题的浓厚兴趣。我一直觉得,面对日益复杂和严峻的环境挑战,单纯依靠经验或者直觉来决策是远远不够的,我们需要更系统、更科学的工具来分析问题、预测趋势,并最终找到最优的解决方案。这本书的书名暗示了它可能提供了一套清晰、可操作的方法论,而非零散的技巧集合。我设想,书中会详细阐述如何构建合适的数学模型,如何验证模型的有效性,以及如何将模型输出转化为实际可行的决策建议。尤其让我期待的是“环境应用”这一部分,我好奇它会涵盖哪些具体领域,例如水资源管理、空气质量预测、生态系统恢复、气候变化适应策略,甚至是废物处理和资源回收等。不同环境问题的背后,往往隐藏着复杂的相互作用和动态变化,如何用数学语言将其精确地描述出来,并在这个模型的基础上进行决策,这本身就是一个巨大的挑战,也是这本书的价值所在。我希望这本书能给我提供一套通用的框架,让我在面对不同的环境问题时,都能从中找到适用的建模思路和决策支持的逻辑。
评分这本书的价值不仅仅在于它提供了方法论,更在于它展现了一种将科学工具应用于解决社会性问题的思维方式。在阅读的过程中,我深刻地体会到,模型构建的过程本身就是一种对环境问题的深入理解和梳理。通过不断地尝试、调整和验证模型,我们被迫去思考问题的每一个组成部分,它们之间的相互作用,以及哪些因素是关键的驱动力。这种“内省式”的研究过程,能够帮助我们打破思维定势,发现那些隐藏在表面现象之下的本质。而且,书中关于“决策支持”的讨论,也让我意识到,科学研究的最终目的是为了更好地服务于人类社会。一个再完美的模型,如果不能转化为实际的决策,那么它的价值将大打折扣。因此,我非常欣赏作者在书中强调的,如何将模型输出转化为可理解、可执行的建议,以及如何与不同的利益相关者进行沟通和协作。这不仅仅是关于数学和工程的知识,更是一种跨学科的沟通和解决问题的能力。这本书为我打开了一个新的视角,让我看到了数学建模在环境治理和可持续发展中的巨大潜力。
评分我对书中关于“环境应用”的案例部分尤为期待,因为我知道,脱离了实际场景的理论研究往往是空中楼阁。这本书能够将“模型驱动的决策支持方法”与“环境应用”相结合,这本身就说明了它具有很强的现实意义。我设想,书中可能会选取一些当前备受关注的环境热点问题,比如城市洪涝的风险评估与预警,基于模型的耕地保护策略,或者如何利用数学模型来优化可再生能源的配置,以实现碳排放的最小化。我希望作者不仅会展示如何构建模型来分析这些问题,更会深入探讨模型结果如何直接指导具体的政策制定和行动方案。例如,一个关于水资源分配的模型,可能能够帮助地方政府在面临干旱时,科学地划分用水指标,减少社会矛盾。又或者,一个关于生物多样性保护的模型,能够为不同保护区域的划定提供量化依据。我非常好奇作者是如何将复杂的数学分析结果,转化为清晰、可操作的“决策支持”建议的,这其中的权衡、沟通和转化过程,往往是科学研究能否真正产生影响力的关键。
评分我收到这本书的时候,就被它厚重的体量和一丝不苟的装帧所震撼。虽然我还没有深入阅读,但仅仅从目录和前言就能感受到作者在内容组织上的深思熟虑。从“基础概念”到“高级模型”再到“案例研究”,这种循序渐进的结构非常适合我这样希望系统学习的读者。我尤其关注书中对“数学建模”的阐述,因为在过去的学习和工作中,我常常被各种复杂的模型搞得头晕脑胀,希望这本书能将抽象的数学概念与实际应用紧密结合,用清晰易懂的语言解释模型背后的逻辑,而不是简单地罗列公式。我设想书中会介绍一些经典的建模技术,比如系统动力学、Agent-based modeling、优化模型等等,并详细解释它们在环境决策中的适用性。我个人对“决策支持”这一环节非常感兴趣,因为很多时候,模型构建出来之后,如何将分析结果转化为有说服力的建议,让非专业人士也能理解并采纳,是让研究成果落地应用的关键。我希望书中能提供一些关于数据可视化、情景分析以及不确定性量化的方法,帮助决策者更好地理解模型输出的含义,并在此基础上做出明智的选择。总而言之,这本书给我的第一印象是严谨、全面且具有很强的实践指导意义。
评分读完这本书的第一部分,我最大的感受就是它并非一本“浅尝辄止”的书,而是真正深入到了模型构建的细节之中。作者在解释如何将现实世界的环境问题抽象成数学模型时,展现了极高的专业素养和丰富的实践经验。我特别喜欢作者对于“模型假设”和“模型验证”的强调,这恰恰是许多初学者容易忽略但至关重要的环节。书中对不同类型模型的优缺点分析,以及在不同环境应用场景下模型的选择指南,也让我受益匪浅。例如,当处理具有反馈回路和非线性关系的系统时,作者推荐了某种类型的模型;而当需要考虑个体行为和空间异质性时,则提出了另一种建模方法。这些细致的指导,让我觉得作者非常了解读者在实际应用中可能遇到的困难。而且,书中穿插的数学推导虽然严谨,但并没有让人感到生涩难懂,作者往往会用清晰的语言解释公式的物理意义,并配合图示来帮助理解。这让我对后续章节中关于“环境应用”的具体案例充满了期待,我相信这些案例将是检验和巩固前面所学理论的最佳途径。
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