Selecting and scheduling interrelated road projects with uncertain demand

Abstract

In transportation systems, the existence of interrelations among components and uncertainties in various elements such as future demand usually complicates the capital budgeting process. This paper proposes a method for evaluating, selecting and scheduling interrelated road projects in an urban network under demand uncertainties. The objective is to optimally determine the selection, sequence and schedule of capacity improvement projects while minimizing the present value of total system cost, including travel time, vehicle operating and safety costs, subject to a cumulative budget flow constraint. The scheduling problem is formulated as a non-linear integer optimization problem within a genetic algorithm that minimizes the present value of the system cost over a planning horizon. The proposed model also includes a design feature which determines the type of improvement at each location. This study constitutes a useful framework for state planners and regional decision makers for the project prioritization process.

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