Nilesh N. Joshi

Equity Metrics With Risk, Performance, and Cost Objectives for the Prioritization of Transportation Projects

Prioritizing and selecting a few critical transportation projects from several competing projects is a multiobjective combinatorial optimization problem (MOCO). Transportation planners and managers are always interested in analyzing and visualizing the tradeoffs involved, but equity issues in distribution of resources are given much less attention. This paper develops a methodology for integrating equity metrics with traditional metrics for planning and prioritizing a large and diverse portfolio of transportation investment projects. The methodology serves to help planners, managers, and engineers to visualize and compare measures of the distributed equity of the allocation along with cost-benefit tradeoffs. It is based on incorporating network-level equity metrics along with traditional metrics in formulating a generic multiobjective combinatorial optimization (MOCO) problem and visualizing multiobjective tradeoffs on the spatial network. A case study of a region demonstrates the use of the methodology in tradeoff analysis for prioritizing and selecting transportation projects. The approach is adaptable to other manufacturing and service industries where consideration of the distributed equity of allocation is an important issue.

Coordination and Diversification of Investments in Multimodal Transportation

Across the nation, there are opportunities to improve multimodal coordination and prioritization of investments among transportation agencies. This article develops a method to coordinate and diversify transportation investments across travel modes and qualitative goals. The method helps decision makers to identify and prioritize investments for multimodal corridors, which involve large-scale coordination of transportation projects across modes. The article describes the developed method in two parts: prioritizing multimodal corridors at a macro level of analysis and coordinating modal projects at a micro level. The benefits of the method include (a) identification of efficient investment alternatives to meet travel demands when considering multiple modes relative to only single modes, (b) direction of funding to the multimodal corridors and modal projects where the needs are most urgent, and (c) increased transparency and accountability of multimodal agencies for funding that can be allocated across multiple modes. The article addresses multimodal transportation planning efforts with systematic, evidence-based approaches to coordinating long-range investments.

Diagramming qualitative goals for multiobjective project selection in large-scale systems

Allocating resources to competing projects is typically driven by multiple quantified objectives generated from the top-level goals of a large-scale system. Analytical tools to aid such allocations have a significant history with many existing methodologies, particularly for optimization and programming within a hierarchy of objective functions. However, the quantified objective functions are known to only partially represent the system goals, and significant challenges remain to preserve relevant considerations that resisted quantification. In particular, the patterns of allocation of resources across the goals may be important to decision-makers, since they could thereby address known, quantifiable issues with some consideration of unknown and emergent issues. This paper develops decision-aiding diagrams of top-level goals and resources that complement the existing multiobjective combinatorial optimization models, to better refine and choose among the optimization-generated portfolios of projects. Adapting existing path diagrams from the social sciences, the newly developed methodology can be subordinate to the generation of Pareto-optimal solutions via the optimization model. The application of path diagrams is demonstrated through a case study of allocating resources to a large-scale system of airports.

Diversification of infrastructure projects for emergent and unknown non‐systematic risks

Allocating resources to competing large‐scale infrastructure projects involves multiple objectives. Traditional decision‐aiding methodologies focus on the trade‐offs among performance and resource objectives. Existing methodologies may fail to account for unknown and emergent risks that are typical of large‐scale infrastructure investment allocation problems. In modern portfolio theory, it is well known that a diversified portfolio can be very effective to reduce non‐systematic risks. The approach of diversification is equally important in choosing robust portfolios of infrastructure projects that may be subject to emergent and unknown risks. In this paper, we demonstrate a methodology to analyze and compare the diversification of portfolios of large‐scale infrastructure projects. We classify and explore several metrics of diversification and integrate them with risk and other performance objectives in a multiobjective approach. We test the new metrics and the methodology in a case study of hundreds of millions of dollars of infrastructure investments. The results suggest that the solutions that consider diversification are more robust to emergent risks, thus, identifying an opportunity to incorporate diversification‐based optimization methodologies to support a variety of problems involving large‐scale infrastructure investments.

Multidimensional Data and Model Uncertainties in Comparing Heterogeneous Benefits of Distributed Transportation Projects

AbstractInvestments in transportation projects are typically justified by diverse potential benefits, including safety, environmental, energy savings, congestion mitigation, and others. There is a need for such benefits to be comparable early in transportation programming, to allocate scarce resources to preliminary engineering. This paper discusses quantitative methods to aid in prioritizing locations of future highway projects. The paper adopts 15 quantitative metrics including crash rate, emergency route access, environmental issues, level of service (LOS), volume-to-capacity ratio, traffic flow, intermodal access, heavy truck usage, unemployment rate, right-of-way use, use of alternative transportation modes, bridge sufficiency rating, and cost effectiveness. This effort contributes to real-world transportation programming and priority setting via analysis of the crash avoidance and other benefits and costs that are expected before project designs are available. The innovation of this paper is in two ...

Prioritizing Highway Construction with a Benefits Analysis

The Virginia Department of Transportation began last year to implement a quantitative methodology as an aid to prioritizing highway construction improvements. The methodology adopts fifteen quantitative metrics used to evaluate the candidate projects. The results of the methodology are used by executive review teams to negotiate, interpret, and support decisions regarding the selection of construction improvements for funding in a

Multiple criteria intelligence tracking for detecting extremes from sequences of risk incidents

1.8B per year construction program. The agency is exploring how the methodology can provide transparency of project selection to the public, agency staff, legislators, and the commonwealth transportation board. The existing metrics need further modeling and aggregation to be meaningful. This effort describes an effort to extend the current prioritization methodology via modeling and uncertainty analysis of the aggregated risk reductions, benefits, and costs associated with the candidate construction improvements. The team developed monetized estimates of benefits in several categories including crashes avoided, travel time saved, fuel uses avoided, and emission avoided. The estimates of benefits were then compared to estimates of project costs, representing the uncertainty of the results as numerical intervals. The developed methodology is demonstrated with project data from nine districts with roughly four hundred candidate projects ranging in cost from

Benefits estimates of highway capital improvements with uncertain parameters.

150K to over

Comparison of single-echelon vs. multi-echelon inventory systems using multi-objective stochastic modelling

100M. The results with our aggregated measures were compared to the results of the prioritization methodology that is currently in use. We conferred regularly with a project steering committee of metropolitan planning organizations, planning district commissions, agency engineers, planners, executives, and others