Resource Allocation Logic Framework to Meet Highway Asset Preservation (2012)

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5 C h a p t e r 1 1.1 Project Background The highway system infrastructure includes several commonly described asset groupings. These groupings typically include pavements and pavement markings, bridge structures, light- ing, traffic control devices, signage, Intelligent Transportation Systems (ITS), drainage struc- tures, traffic barriers, landscaping, noise barriers, and rest areas. State DOTs manage various programs to maintain, preserve, and rehabilitate these assets to extend their useful life and ensure that they can provide safe and acceptable service throughout it. State DOTs have to balance vari- ous considerations and points of view on priorities as they allocate (usually) scarce resources across and within their highway management programs. Overall, it is challenging for states to balance multiple priorities; to optimize the allocation of these resources to meet expectations on service performance; and, at the same time, to maximize expected useful life from existing assets. Large-scale replacement of failed or badly deteriorated highway assets is far beyond the means of most agencies and will be for the foreseeable future. The challenge in developing a logic framework to support allocation decisions across the wide variety of highway asset groupings has not been met to date. Many decision-support and planning tools are available to support project selection, estimation, accounting, and operational deci- sions, but these tools tend to be specialized and focused technically on particular assets. There is no widely accepted logic framework to address resource allocation decisions that account for a broader (multi-asset) view of preservation program needs. The overarching goal of the NCHRP Project 14-21, “Resource Allocation Framework to Meet Highway Asset Preservation Needs,” is to develop an analysis framework that state DOTs can use as a guide and tool to allocate highway system preservation resources across various principal asset groupings, preservation activities, and regions within their jurisdiction. To achieve this goal, this project has three main objectives: 1. Develop and describe a practical logic framework (including principles, objective functions, and constraints) using operations research methodologies. 2. Develop a logic process to apply the logic framework. 3. Develop a demonstration application of the logic framework using example cases and data. To accomplish these objectives and ensure the success of this project, the research team devel- oped and implemented a detailed technical process (shown in Figure 1-1) to guide the research plan, analyses, and activities. 1. Formulate the Resource Allocation Problem. As a first step, the research team studied the relevant information and developed a well-defined statement of the highway preservation resource allocation problem to be considered. This study included determining the appropriate objectives, the constraints on what can be done, and interrelationships among the areas to Introduction

6 resource allocation Logic Framework for highway asset preservation study. This was a crucial process, because it greatly affected the relevance and practicality of the research results. 2. Construct a Mathematical Model. After defining the decision factors for resource allocation, the research team formulated the resource allocation problem for analysis and solution, to construct a mathematical model that represents the essence of the problem. The mathemati- cal model broadly defines the problem and guides the computational solutions. This tool aided in making the overall structure of the problem comprehensible and revealed important cause-and-effect relationships. 3. Derive a Solution from the Model. After formulating the mathematical model, the next step was to derive a solution from this model. This is an analytical step in which one of the stan- dard algorithms of operations research was applied. To ensure the model is practical and can be easily used by DOT managers and applied in broad programmatic investment decision processes, the analysis and linear optimization model were developed using Microsoft Office Excel and Microsoft Solver. 4. Develop Application Procedures. In parallel with developing a logic framework for the resource allocation problem, the team developed appropriate processes and logic to put the logic framework to practical use, recognizing that there is a significant variety of user approaches and program structures for preservation resource allocation. These processes will help to guide state DOTs in optimizing resource allocation in a way that recognizes preserva- tion resource needs and reflects programmatic priorities and system performance goals for asset condition and life. 5. Test and Demonstrate the Logic Framework. An initial solution model was developed for demonstration of the logic based on plausible state preservation program structures and underlying data sets for asset inventories, costs, deterioration rates, asset condition, and per- formance goals. This data set was adapted from real state DOT data gathered from document research and prior project experience of the research team. This solution model was dem- onstrated for the NCHRP Project 14-21 panel, and then further tested in two case applica- tions and a workshop with panel members and resource management subject matter experts (SME). These cases engaged real-world processes and program structures extant at two state DOTs. After the casework and workshop, numerous refinements and streamlining changes were made to the logic framework based on the findings. The refinements were made to pro- vide greater flexibility and scalability in the preservation program asset and activity taxonomies that can be applied as well as to accommodate realities in the availability and quality of key data Formulate Problem Construct Mathematical Model Derive Solution Develop Application Procedures Test Framework Finalize Framework Figure 1-1. NCHRP Project 14-21 Resource Allocation Logic Framework technical approach overview.

Introduction 7 sets and estimates needed to fully exercise the optimization potential of the solution. The latter accommodation will support useful application of the logic framework with which data and estimates are presently available while enabling the phasing in of more features when that data is developed. 6. Finalize the Framework. Based on the results of the case studies and the workshop, the research team developed a streamlined Excel-based solution model that permits users to enter appropriate preservation program taxonomies, information on available data sets, and program priorities and goals. The model is scalable to a wide set of user-defined asset/activity groupings (AAG) and multiple districts (statewide allocations can be rolled up from district totals or computed as a “single” district). The model incorporates comments and findings from the workshop, and it offers optimized allocations across all AAGs that are supported by data or reasonable estimates of inventory, average condition, deterioration rates, and unit costs. For specific AAGs that are not supported by this data or reasonable estimates for these factors, alternative optimization approaches are built in. Particulars on these options are treated extensively in Chapter 6, and example versions of the model solutions are found in the text and Appendix E. 1.2 Organization of the Report This report summarizes the methodology for developing an analysis framework that state DOTs can use as a guide to allocate limited resources to maintain crucial transportation and highway assets. The following describes the organization of this report: • Chapter 2: Literature Review. This chapter addresses the current state-of-the-practice in preservation resource allocation. • Chapter 3: Resource Allocation Solution Context and Requirements. This chapter describes the decisionmaking context for preservation resource allocation within state DOTs. This includes determining the appropriate objectives and the constraints on the process. • Chapter 4: Resource Allocation Logic Framework Development. This chapter formulates the resource allocation computational model as a basis for optimization. • Chapter 5: Case Studies and Workshop Findings. This chapter describes the key findings from the case studies and workshop that were conducted to test application of the Resource Allocation Logic Framework. • Chapter 6: Resource Allocation Logic Framework. This chapter describes the solutions developed to optimize resource allocation. Assumptions, formulae, data and estimates, pri- oritization, and optimization logic are discussed and detailed with examples. It provides alter- native approaches for application of the logic framework as well as key considerations in data collection and estimation of key factors, including deterioration and unit costs. A companion demonstration model (in Excel workbook format) is available on the NCHRP Project 14-21 web page at www.trb.org. • Chapter 7: Conclusion. This chapter wraps up key lessons learned from the research and case- work, summarizing a number of key challenges for DOTs to address in adopting the Resource Allocation Logic Framework in support of agencies’ regular allocation processes. Suggestions are offered to facilitate understanding, acceptance, and deployment of the logic framework. • Appendix A. Literature Review Summary • Appendix B. State DOT Interview Guidebook • Appendix C. References • Appendix D. Acronyms • Appendix E. Instructions to Activate Solver in Excel Program