Integrated Herfindahl-Hirschman Index, Compromise Programming, and ε-Constraint Method For Multicriteria Performance-Based Transportation Budget Allocation

This paper introduces a new method for multicriteria performance-based transportation budget allocation. First, the Herfindahl-Hirschman Index (HHI) that has long been used in economics for measuring the level of monopolization in a marketplace is employed to derive the relative weights of multiple non-commensurable transportation performance criteria. Next, a compromise programming (CP) model is formulated to help transform the multicriteria optimization formulation for transportation budget allocation to a single-objective optimization model solvable by minimizing the Chebyshev distance to the ideal levels of performance targets associated with individual performance criteria. Finally, the epsilon-constraint trade-off analysis method is incorporated into the combined use of HHI and CP framework to iteratively derive the optimal decision outcome. Six-year data on candidate investment projects proposed for a U.S. state-maintained rural Interstate highway system along with data details of the available budget is used in a computational study for method application. Comparative analysis of decision outcomes is conducted with the STEP method for cross validation. It has revealed that the proposed HHI-CP epsilon-constraint method outperforms the existing method and can be adopted by state and local transportation agencies to carry out effective budget allocation.

Automated summary

This paper introduces a new method for multicriteria performance-based transportation budget allocation, utilizing HHI index and compromise programming model to iteratively derive optimal decision outcomes. The study shows that this method outperforms existing methods and can be used for effective budget allocation by state and local transportation agencies.