Ivan Damnjanovic

Reliability-Based Optimization Models for Scheduling Pavement Rehabilitation

: Deteriorating pavements require timely application of rehabilitation actions. This article presents reliability-based optimization models for scheduling rehabilitation actions for flexible pavements. The pavement reliability and the effect of rehabilitation actions are modeled using parametric fragility curves based on simulated pavement responses. Three models are presented: MIN-C, a model that minimizes the cost where the target reliability is set as a constraint; MAX-R, a model that maximizes the cumulative life-cycle reliability where the budget is set as a constraint; and minimize cost and maximize reliability (MINMAX), a multi-objective model that determines Pareto optimal solutions to reliability-cost trade-off. As the multi-objective optimization model is nonlinear and nonconvex, the solution approach is based on a multi-objective genetic algorithm (MOGA). The results from a numerical example show that the developed optimization model can be used efficiently in determining optimal rehabilitation strategies and cost-reliability trade-offs.

Design and Management Strategies for Mixed Public Private Transportation Networks: A Meta-Heuristic Approach

This article presents a new multi-objective mathematical programming framework to model interactions between public and private sectors in constructing and maintaining highway networks using the build, operate, and transfer scheme. In this study, private companies are assumed to have a degree of control over highway sections on which they perform maintenance and rehabilitation and capacity expansion activities. Private investors recover the cost of construction by levying tolls. The public agency is assumed to maintain the rest of the network with the aim of minimizing total system generalized cost. The bi-directional impact of roadway utilization on deterioration and deterioration on utilization is modeled in this study. The model accounts for route choice of users and all users are assumed to choose routes that have equal and minimal experienced generalized cost. The nonconvex and discontinuous multi-objective mathematical program is solved using nondominant sorting genetic algorithm-II and the pareto-optimal trade-off surface between the profit of the private company and the total system cost is generated. Computational runs are conducted to demonstrate the suitability and flexibility of the developed framework in modeling various policy decisions such as the presence of noncompete clauses.

Framework for Studying Emerging Policy Issues Associated with PHEVs in Managing Coupled Power and Transportation Systems

As gasoline prices rise, plug-in hybrid electric vehicles (PHEVs) may be quickly becoming an economical choice for transportation. This paper explores the policy issues associated with widespread PHEV deployment. These include improving the electric grid performance, enhancing penetration of renewable energy sources and improving energy security, managing air quality and carbon footprint, creating new markets, and planning energy exchange stations that allow for driver flexibility. Coupling the transportation and power systems through PHEVs presents both challenges and opportunities that involve multidisciplinary approach, and proper policy is necessary to take maximize benefit and avoid pitfalls. A multi-layered modeling approach (including transportation, power systems, cognitive behavior, and economic feasibility) that is spatially and temporally encompassing is proposed for evaluating PHEV policy implications.

Development of Structural Condition Index to Support Pavement Maintenance and Rehabilitation Decisions at Network Level

Every year, state highway agencies apply large amounts of seal coats and thin overlays to pavements to improve the surface condition, but these measures do not successfully address the problem. Overall pavement condition continues to deteriorate because of the structural deformation of pavement layers and the subgrade. To make effective decisions about the type of treatment needed, one should take into consideration the structural condition of a pavement. Several different structural estimators can be calculated by using falling weight deflectometer data and information stored in the Pavement Management Information System (PMIS) at the Texas Department of Transportation. The analysis considers pavement modulus and structural number as the structural estimators of a pavement. The evaluation method is based on the sensitivity of the structural estimators to deterioration descriptors. The deterioration per equivalent single-axle load of all major scores stored in the Texas PMIS is proposed as the primary indicator of pavement deterioration. In addition, the use of the structural condition index is recommended as a screening tool to discriminate between pavements that need structural reinforcement and those that do not. This index is calibrated for use in maintenance and rehabilitation analysis at the network level.

Valuation of strategic network flexibility in development of toll road projects

A reliable, cost‐effective and safe transportation system is essential to economic growth. To keep pace with demands for network capacity, revenue‐generating projects are increasingly being used to complement the current procurement practices and lessen the pressure on public finances. In such transportation networks where there exists a mix of free access links and links with user fees, network interconnectivity is an important component of project valuation. A bilevel stochastic recourse model for valuating network flexibility is formulated. A key component of the model is consideration of network‐based managerial flexibility in context of the upper level project valuation objective and the lower level network user equilibrium solution under demand uncertainty. The results from a test network, for which a closed form solution is possible, indicate that the value of network flexibility directly depends on initial network conditions, variance in future travel demand and toll pricing decisions.

Impact of crude oil market behaviour on unit bid prices: the evidence from the highway construction sector

It is well known that the cost of highway construction is affected by the cost of crude oil. While this relationship is highly visible for construction items such as asphalt cement (a by‐product in the process of refining oil), the effects of the crude oil prices on the cost of other construction items, such as concrete cement or construction operations are less direct, but equally important. For unit‐based contracts without price adjustment clauses, this relationship is of a particular significance. In fact, an increase in price of fuel could result in substantial losses, as contractors are not protected. Hence, to hedge against this risk, contractors are likely to incorporate a premium in bid prices to manage project risks. The objective of this paper is to investigate the evidence of this behaviour. New evidence shows that the expected change in oil prices (the difference between future and spot price) and the implied volatility in the oil market affect the price of bid items for contracts without price adjustment clauses. Such results allow for more effective implementation of risk management on project‐ and programme‐level basis.

Effects of Pavement Spatial Variability on Contractor’s Management Strategies

Performance-based maintenance contracts are becoming an increasingly popular method of outsourcing pavement maintenance work. These contracts transfer performance-related risks to contractors with the objective of reducing the total cost of maintenance over the pavement life cycle by leveraging on the efficiencies of private sector management. In such contractual settings, transportation agencies hedge their exposure to poorly performing pavements that require frequent attention. However, this comes with a price. Contractors price in their bids a premium to account for such scenarios. This paper presents a model for contractors to determine optimal management strategies by taking into account the inherent spatial variability in pavements structural characteristics. The model considers a tradeoff between economies of scale associated with managing longer pavement sections and the risk reduction benefits with managing relatively smaller, e.g., more homogeneous sections. The results indicate that the length of optimal management sections depends not only on the expected contract penalty costs (disincentive costs), but also the ability of the contractor to explore economies of scale. The model is illustrated using typical data available to transportation agencies.

Modeling Pavement Fragility

Pavement performance models are the key to efficient designs and effective management practices. Over the years, a number of researchers have developed reliability models to account for the uncertainty in pavement responses and utilization patterns. However, these efforts were mostly directed toward coupled capacity-demand limit state functions that do not take into account the discontinuities after the application of rehabilitation actions (e.g., overlays). The aim of this paper is to develop a pavement fragility modeling framework that accounts for the effects of the rehabilitation actions. The fragility, defined as the conditional probability of failure given a unit level of utilization, uncouples the reliability function into the capacity and demand functions, which are two separate areas of study in pavement engineering. Closed-form approximations of the fragility curves are developed to illustrate the process and allow for seamless integration in design and management optimization models.

Educational Prediction Markets: Construction Project Management Case Study

Effective teaching of engineering concepts relies both on carefully designed lesson plans that meet specific learning outcomes, and on classroom activities that students find engaging. Without student engagement, even the best designed plans will fail to meet their outcomes. In other words, students need to be actively involved in the learning process. The objective of this paper is to present a case study of applying a novel active learning method, specifically educational prediction markets (EPM), for teaching project management classes at a major research university. This method was investigated for its effectiveness in engaging students, as well as promoting learning of probabilistic reasoning without explicit teaching. Student surveys, following the EPM implementation, revealed both advantages and disadvantages. The two key benefits reported by the students were: a) providing better connections between the materials taught in the class and realities of construction projects, and b) increasing overall interest and enthusiasm in learning about project risk management due to the game-like nature of the process. The main disadvantage was disengagement by a subset of students due to perceptions that fellow students were manipulating the market results.

Market-implied spread for earthquake CAT bonds: financial implications of engineering decisions.

In the event of natural and man-made disasters, owners of large-scale infrastructure facilities (assets) need contingency plans to effectively restore the operations within the acceptable timescales. Traditionally, the insurance sector provides the coverage against potential losses. However, there are many problems associated with this traditional approach to risk transfer including counterparty risk and litigation. Recently, a number of innovative risk mitigation methods, termed alternative risk transfer (ART) methods, have been introduced to address these problems. One of the most important ART methods is catastrophe (CAT) bonds. The objective of this article is to develop an integrative model that links engineering design parameters with financial indicators including spread and bond rating. The developed framework is based on a four-step structural loss model and transformed survival model to determine expected excess returns. We illustrate the framework for a seismically designed bridge using two unique CAT bond contracts. The results show a nonlinear relationship between engineering design parameters and market-implied spread.