A TWO-STAGE OPTIMIZATION MODEL FOR OPTIMAL HIGHWAY TRANSPORTATION INVESTMENT DECISION-MAKING

The optimization formulation for highway project selection is known as the capital budgeting problem, which can be generalized as a zero/one integer knapsack problem. The objective is to select a subset from all economically feasible candidate projects to achieve maximized overall benefits under budget and other constraints. This paper introduces a two-stage optimization model extended from the existing zero/one knapsack formulation to explicitly address the issue of risk associated with project benefits. At the first stage, the Markowitz mean-variance model is employed to find the lowest total risks in the benefits of all proposed projects. At the second stage, the knapsack model is enhanced by adding the first-stage optimization solution as one more optimization constraint. The proposed model is applied for a six-year state-wide Interstate highway programming and project selection. Comparisons are made in the consistency of projects selection results generated from the proposed model and the existing knapsack formulation.