政府投资项目决策系统演化机理及其仿真研究
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摘要
政府投资项目决策工作是该类项目投资建设工作中的重要一环,对投资项目能否取得预期的经济、社会效益起着关键作用。由于建设项目具有不可逆转性,因此决策主体以及与决策相关各要素组成的决策系统对于决策项目的成败关系重大。本文基于复杂适应系统理论,力图探究政府投资项目决策系统的复杂特性和复杂适应性内涵,以及政府投资项目决策系统的演化机理,以期为政府投资项目决策的科学化、合理化提供新的思路。
本文的主要研究工作包括：
(1)构建由决策主体和决策协同要素两部分组成的政府投资项目决策系统,探究该决策系统的复杂性,基于复杂适应系统理论从决策系统的特性和机制两个方面论述决策系统的复杂适应性,并证明决策系统是一个复杂适应系统,为论证决策系统演化机理奠定基础。
(2)探求决策系统演化的内在动因。适应性主体是复杂适应系统的核心组成要素,也是系统演化的主体。决策系统的适应性主体就是决策系统演化的内在动因即决策系统的演化动力。
(3)构建决策系统的演化环境。信息资源条件即环境的支撑是演化的基础。演化环境构建结构包括内有激励约束机制和责任治理机制外有政法环境和社会环境四个组成部分。
(4)从适应性学习机理和涌现机理两个方面论证决策系统的演化机理。决策系统的适应性学习机理通过遗传算法的两个步骤——信用分派机制和新规则的发现机制进行论述。对决策系统的涌现机理中环境效应、结构效应和规模效应等三个方面进行论述,并构建决策系统的层次涌现模型用来说明其涌现的本质。
(5)对决策系统稳态进行动力学分析。本文将基于系统动力学从决策主体反馈机制和决策系统要素的反馈机制对决策系统的稳态进行动力学分析。
(6)在基于多Agent系统建模理论的指导下实现了决策系统在复杂适应系统仿真平台NetLogo上的实验仿真。
通过以上各项研究工作本文得出以下结论：政府投资项目决策是一个复杂的系统工程。决策系统是一个复杂适应系统,它的结构是个复杂的、多维的立体关联体。决策系统在内在动因和演化环境的共同作用下发生适应性学习和涌现,从而实现系统的演化。演化功能促使决策系统成为一个能够科学、合理、高效完成决策任务的整体。
本文的主要创新点体现在：从一个全新的理论视角揭示由决策主体和决策协同要素组成的政府投资项目决策系统经过适应性学习和涌现达到稳定状态的演化规律；并利用软件实现系统演化仿真分析。
但由于篇幅限制,以及水平和时间有限,本文还有不足之处,有待做进一步研究。
Decision-making on government investment projects is the construction of such investment that is an important part of the investment project work. Decision-making work that can achieve the desired economic and social benefits may play a key role. Since the irreversibility of the construction project, so the decision-making system including the decision-making body and the various elements associated with decision-making is for making the success of the project at stake. Based on the theory of complex adaptive systems, government investment project sought to explore the complex nature of decision-making system and complex adaptive content, as well as government investment project decision-making mechanism of the evolution of the system, with a view to investment projects for the government decision-making scientific and reasonable to provide new ideas.
This major research work includes:
(1) Decision-making system of government investment project is composed of two elements of decision-making body and the various elements associated with decision-making, to explore the complexity of the decision-making system, based on the theory of complex adaptive systems characteristics from decision-making system and discusses two aspects of decision-making mechanisms of complex adaptive systems sex, and that decision-making system is a complex adaptive system, the mechanism for the evolution of proof lay the foundation for decision-making system.
(2)The intrinsic motivation of the evolution of decision-making system will be explored. The adaptability body is the main core of elements composed of complex adaptive systems, but also is body of the evolution of the main system. The adaptability body of decision-making system is the main intrinsic motivation about decision-making systems evolution and that is the evolution dynamic of decision-making system.
(3) The environment of the evolution of decision-making system will be built. Information resource condition that is support of the environment is the basis for evolution. The structure of the environment of evolution will include the four components of the mechanisms for incentive and restraint and the mechanisms for responsibilities inside, and the political and legal environment, governance and social environment outside.
(4) The evolution of mechanisms of decision-making system is proved from the adaptive learning mechanism and genetic algorithm. Adaptive learning mechanism of decision-making system by genetic algorithm in two steps-credit assignment mechanism and the new discovery rules are discussed. Mechanism for decision-making system in the emergence of environmental effects, structural effects and size effects are discussed in three areas, and build decision-making system-level model used to explain the emergence of the emerging nature.
(5) Dynamic analysis for decision-making system in steady-state, which will be analysis that is based on system dynamics feedback mechanism from the decision-making body and decision-making elements.
(6) Under the guidance of the theory of Multi-Agent-based modeling system, the simulation experiments of decision-making system will be implemented on the NetLogo which is platform about simulation experiments of complex adaptive systems.
This dissertation including the following conclusions:government investment project decision-making is the complex system engineering. The decision-making system is the complex adaptive system that the system structure is a complex and multi-dimensional association body. The adaptive learning and the emergence of decision-making system will occur under the joint action of the evolution dynamics insidely and the evolution environment outsidely, in order to achieve the system evolution. The evolution function will promote decision-making system to become the whole which is scientific, rational and completing decision-making tasks efficiently.
The main innovation of this dissertation is reflected in:The dissertation reveals Decision-making system of government investment project which is composed of two elements of decision-making body and the various elements associated with decision-making evolutes through adaptive learning and the emergence of steady state from the new theory perspective; and the simulation for decision-making system is the use of simulation software.
However, due to the limited on space constraints, my level and time, this dissertation is inadequate. This dissertation needs to be improvement and optimization furtherly.
本文的主要研究工作包括：
(1)构建由决策主体和决策协同要素两部分组成的政府投资项目决策系统,探究该决策系统的复杂性,基于复杂适应系统理论从决策系统的特性和机制两个方面论述决策系统的复杂适应性,并证明决策系统是一个复杂适应系统,为论证决策系统演化机理奠定基础。
(2)探求决策系统演化的内在动因。适应性主体是复杂适应系统的核心组成要素,也是系统演化的主体。决策系统的适应性主体就是决策系统演化的内在动因即决策系统的演化动力。
(3)构建决策系统的演化环境。信息资源条件即环境的支撑是演化的基础。演化环境构建结构包括内有激励约束机制和责任治理机制外有政法环境和社会环境四个组成部分。
(4)从适应性学习机理和涌现机理两个方面论证决策系统的演化机理。决策系统的适应性学习机理通过遗传算法的两个步骤——信用分派机制和新规则的发现机制进行论述。对决策系统的涌现机理中环境效应、结构效应和规模效应等三个方面进行论述,并构建决策系统的层次涌现模型用来说明其涌现的本质。
(5)对决策系统稳态进行动力学分析。本文将基于系统动力学从决策主体反馈机制和决策系统要素的反馈机制对决策系统的稳态进行动力学分析。
(6)在基于多Agent系统建模理论的指导下实现了决策系统在复杂适应系统仿真平台NetLogo上的实验仿真。
通过以上各项研究工作本文得出以下结论：政府投资项目决策是一个复杂的系统工程。决策系统是一个复杂适应系统,它的结构是个复杂的、多维的立体关联体。决策系统在内在动因和演化环境的共同作用下发生适应性学习和涌现,从而实现系统的演化。演化功能促使决策系统成为一个能够科学、合理、高效完成决策任务的整体。
本文的主要创新点体现在：从一个全新的理论视角揭示由决策主体和决策协同要素组成的政府投资项目决策系统经过适应性学习和涌现达到稳定状态的演化规律；并利用软件实现系统演化仿真分析。
但由于篇幅限制,以及水平和时间有限,本文还有不足之处,有待做进一步研究。
Decision-making on government investment projects is the construction of such investment that is an important part of the investment project work. Decision-making work that can achieve the desired economic and social benefits may play a key role. Since the irreversibility of the construction project, so the decision-making system including the decision-making body and the various elements associated with decision-making is for making the success of the project at stake. Based on the theory of complex adaptive systems, government investment project sought to explore the complex nature of decision-making system and complex adaptive content, as well as government investment project decision-making mechanism of the evolution of the system, with a view to investment projects for the government decision-making scientific and reasonable to provide new ideas.
This major research work includes:
(1) Decision-making system of government investment project is composed of two elements of decision-making body and the various elements associated with decision-making, to explore the complexity of the decision-making system, based on the theory of complex adaptive systems characteristics from decision-making system and discusses two aspects of decision-making mechanisms of complex adaptive systems sex, and that decision-making system is a complex adaptive system, the mechanism for the evolution of proof lay the foundation for decision-making system.
(2)The intrinsic motivation of the evolution of decision-making system will be explored. The adaptability body is the main core of elements composed of complex adaptive systems, but also is body of the evolution of the main system. The adaptability body of decision-making system is the main intrinsic motivation about decision-making systems evolution and that is the evolution dynamic of decision-making system.
(3) The environment of the evolution of decision-making system will be built. Information resource condition that is support of the environment is the basis for evolution. The structure of the environment of evolution will include the four components of the mechanisms for incentive and restraint and the mechanisms for responsibilities inside, and the political and legal environment, governance and social environment outside.
(4) The evolution of mechanisms of decision-making system is proved from the adaptive learning mechanism and genetic algorithm. Adaptive learning mechanism of decision-making system by genetic algorithm in two steps-credit assignment mechanism and the new discovery rules are discussed. Mechanism for decision-making system in the emergence of environmental effects, structural effects and size effects are discussed in three areas, and build decision-making system-level model used to explain the emergence of the emerging nature.
(5) Dynamic analysis for decision-making system in steady-state, which will be analysis that is based on system dynamics feedback mechanism from the decision-making body and decision-making elements.
(6) Under the guidance of the theory of Multi-Agent-based modeling system, the simulation experiments of decision-making system will be implemented on the NetLogo which is platform about simulation experiments of complex adaptive systems.
This dissertation including the following conclusions:government investment project decision-making is the complex system engineering. The decision-making system is the complex adaptive system that the system structure is a complex and multi-dimensional association body. The adaptive learning and the emergence of decision-making system will occur under the joint action of the evolution dynamics insidely and the evolution environment outsidely, in order to achieve the system evolution. The evolution function will promote decision-making system to become the whole which is scientific, rational and completing decision-making tasks efficiently.
The main innovation of this dissertation is reflected in:The dissertation reveals Decision-making system of government investment project which is composed of two elements of decision-making body and the various elements associated with decision-making evolutes through adaptive learning and the emergence of steady state from the new theory perspective; and the simulation for decision-making system is the use of simulation software.
However, due to the limited on space constraints, my level and time, this dissertation is inadequate. This dissertation needs to be improvement and optimization furtherly.
引文
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