Collaborative Proposal: A Multilayer Capital Budgeting Model for Comparative Analyses of Infrastructure Networks

摘要建议：CMS-0116107 PI：Terry Friesz机构：乔治梅森大学日期：2001年7月25日摘要：一个用于基础设施网络比较分析的多层次资本预算模型本项目研究了大规模、多层次基础设施网络的动态资本预算问题，这些网络包括交通网络、水利网络、能源网络、电信网络、金融网络，具体而言，本项目的目标是开发一个多层动态网络资本预算模型，该模型可用于量化基础设施网络的协调规划和设计可能带来的成本节约和效率提高。过去，基础设施网络只被孤立地考虑。因此，该项目是发展基础设施网络设计的综合理论和新一代基础设施决策支持系统的第一步，该系统能够识别和促进各个网络层之间的协同作用。反映物理，财务，经济和信息相互依赖性的约束用于耦合网络层。网络活动进一步受到流守恒、资源和非负性约束的约束。状态动力学识别活跃在各个网络层上的个体代理的替代博弈行为，因此可以考虑关于网络上完美和不完美经济竞争性质的不同假设。目标是最大限度地提高净经济效益的现值。这个目标是结合上述约束和状态动态创建一个家庭的微分游戏，制定为最优控制模型。这些模型可以用来确定在时间和空间上基础设施资本投资的最有效分配。本项目中使用的研究方法结合了定性分析和非瞬态求解技术。也就是说，经典的数值方法和组合优化/基于代理的仿真（ABS）模型被认为是。特别是，微分博弈模型被用来验证ABS模型。在这方面的一个关键任务是模型动态参数值的灵敏度的调查。虽然一个实际的大都市基础设施系统的案例研究超出了这个初步研究的范围，我们也将开发一个实验设计的优化/ABS模型的验证。我们还将描述如何使用该模型来制定一个中等规模城市的基础设施系统的最佳容量扩展计划。

ABSTRACTProposal: CMS-0116107PI: Terry FrieszInstitution: George Mason UniversityDate: July 25, 2001Abstract: A Multilayer Capital Budgeting Model for Comparative analyses of Infrastructure NetworksThis project addresses the dynamic capital budgeting problem for large scale, multi-layer infrastructure networks, comprised of transportation networks, water networks, energy networks, telecommunications networks, financial networks, and genera data flow networks.Specifically, the objective of this project is to develop a multi-layer dynamic network capital budgeting model that can be used to quantify the cost savings and efficiency enhancements that might accrue from the coordinated planning and design of infrastructure networks. In the past, infrastructure networks have only been considered in isolation. As such this project is the first step toward developing both a comprehensive theory of infrastructure network design and a new generation of infrastructure decision support systems capable of identifying and promoting synergies among individual network layers.Constraints reflecting physical, financial, economic, and information interdependencies are used to couple network layers. Network activities are further constrained by flow conservation, resource and non-negativity constraints. The state dynamics recognize the alternative gaming behaviors of individual agents active on the various network layers, so that different assumptions regarding the nature of perfect and imperfect economic competition over networks can be considered. The objective is to maximize the present value of net economic benefits. This objective is combined with the aforementioned constraints and state dynamics to create a family of differential games that are formulated as optimal control models. These models can be used to determine the most efficient allocation of infrastructure capital investments over both time and space.The research approach used in this project combines qualitative analysis and nontranditional solution techniques. That is, both classical numerical methods and combined optimization/agent-based simulation (ABS) models are considered. In particular, the differential game model is used to validate the ABS model. A key task in this regard is the investigation of the sensitivity of the model dynamics to parameter values. Although a case study of an actual metropolitan infrastructure system is beyond the scope of this initial research, we will also develop an experimental design for validation of the optimization/ABS model. We will also describe how the model may be used to develop an optimal capacity expansion plan for the infrastructure systems of a medium size city.