Proposal: CMS-0116342 PI: Srinivas Peeta Institution: Purdue Research Foundation Date: July 25, 2001
Abstract: A Multilayer Capital Budgeting Model for Comparative analyses of Infrastructure Networks
This 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.
