Efficient highway asset management that provides
tools to facilitate a more organized, logical
approach to achieve truly optimal investment
decisions becomes increasingly important. Highway
project evaluation and project selection are key
steps in the investment decision-making process.
This text introduces a generalized methodology for
highway project evaluation that offers flexibility
for the decision-maker to consider any combination
of input factors such as project costs, traffic
demand, and discount rates under certainty, risk or
uncertainty in the estimation of project-level
agency and user benefits. It could estimate the
amount of benefits associated with
project sub-level agency or user benefit items (if
further separable) under certainty, risk or
uncertainty in accordance with available
information. It also proposes stochastic
optimization models, along with an efficient
solution algorithm, for project selection that
explicitly address budget uncertainty. The new
methodology and models can be adopted by
transportation agencies to achieve globally optimal
investment decisions.
tools to facilitate a more organized, logical
approach to achieve truly optimal investment
decisions becomes increasingly important. Highway
project evaluation and project selection are key
steps in the investment decision-making process.
This text introduces a generalized methodology for
highway project evaluation that offers flexibility
for the decision-maker to consider any combination
of input factors such as project costs, traffic
demand, and discount rates under certainty, risk or
uncertainty in the estimation of project-level
agency and user benefits. It could estimate the
amount of benefits associated with
project sub-level agency or user benefit items (if
further separable) under certainty, risk or
uncertainty in accordance with available
information. It also proposes stochastic
optimization models, along with an efficient
solution algorithm, for project selection that
explicitly address budget uncertainty. The new
methodology and models can be adopted by
transportation agencies to achieve globally optimal
investment decisions.