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Abstract
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 decisionmaking
framework was found to be adaptable to this typical investment case study.