Developing Decision-Making Process for Prioritizing Potential Alternatives of Truck Management Strategies

The objective of this dissertation is to develop a decision-making
method framework for prioritizing various potential alternatives of
truck management strategies using Multi-Criteria Decision-Making (MCDM)
method. The motivation of this research is derived from the need of
investigating and evaluating all likely impacts resulting from the
implementation of truck strategies. Since the conventional evaluation
methods such as the cost-benefit analysis can only be considered impacts
involving monetary scales, we believe these are insufficient to
investigate the all likely impacts. Our method is developed in order to
address all measures that can transformable and non-transformable as
well as to reflect decision-makers’ priorities of the problem. As a
result, two main objectives are accomplished in our study. The first is
to investigate the all likely impacts resulting from the implementation
of truck management strategies by performing a specific case study of
before and after cases using traffic simulation models. A key feature of
this part is to analyze various performance measures. They include both
measures that can transformable and non-transformable into monetary
costs as well as can reflect the standpoints of the public and the
private sectors. Secondly, a decision-making method is developed using
the Analytical Hierarchy Process (AHP) method which is one of popular
multi-criteria decision-making (MCDM) methods. This method enables the
judgments and preferences of decision-makers to be quantified based on
the relative importance of their own criteria, and to allow a
quantitative interpretation from others. Another important contribution
of our work is to suggest a “score-allocation” method which is a
normalization technique. Since quantitative measurements have different
scales, we need to incorporate these measurements into a single value.
This method allows decision-makers easily to facilitate comparisons
among potential alternatives. We believe that scores across alternatives
provide the argument to prioritize potential alternatives of truck
strategies.