This paper presents a framework based on multi-objective optimization that can be used to generate and analyze the most desirable transportation investment options based on their objectives and constraints. The framework, which is based on the surrogate worth trade-off analysis, could be applied to both discrete or continuous decision-problem scenarios. In a discrete problem, a pre-defined set of alternatives is available, whereas continuous problems are not characterized by a pre-defined set of alternatives. This framework was applied with the data generated for a Capital Beltway Corridor investment study. The multi-objective decision-making framework was found to be adaptable to this typical investment case study.
