Flexible aggregation in multiple attribute decision making: Application to the Kuranda Range Road Upgrade

The conventional method of aggregating the satisfaction of transport projects with respect to multiple attributes is commonly some variant of Simple Additive Weighting (SAW), which involves the sum of products of standardized outcomes of projects with respect to attributes and attribute importance weights. It is suggested that alternative forms of aggregation might be more useful, in particular, the Ordered Weighted Averaging (OWA) operator introduced by Yager (1988). Attribute importance weights and satisfaction of attributes by projects may be aggregated prior to aggregation via an OWA operator. In this case OWA operator weights may be based on the "attitudinal character of the decision maker expressed in terms of the degree of "orness and "andness of the aggregation. A well-known approach is maximum entropy aggregation, in which weights are derived to be as "even (or as minimally dispersed) as a possible subject to satisfying a given "orness or "andness constraint. Recently, aggregation processes have been proposed by Larsen (199920022003) which have several desirable properties and also may be considered as alternative forms of aggregation. An example is given relating to the Kuranda Range Road upgrade (Queensland, Australia) which is limited by grade, poor overtaking opportunities, poor horizontal alignment, and other constraints, and the road is expected to become increasingly congested over the next few years. A more flexible Multiple Attribute Decision Making is used to identify a "best project from a set of four alternative projects

ESTIMATING PATRONAGE FOR A FEASIBILITY STUDY OF HIGH-SPEED RAIL IN THAILAND

A feasibility study of a system of high-speed rail lines for the kingdom of Thailand is described. Absent comprehensive local data and any intercity forecasting models for the nation, an incremental demand model and an incremental mode-choice model were chosen as the modeling techniques to use for the study. The incremental demand model used variables of population, gross provincial product, and the log sum term of level of service from the mode-choice model. The mode-choice model itself was synthesized using parameter values from similar efforts in other countries, adjusted to local currency values and income per capita. The steps taken to estimate base-year demand and market shares are described, and the application of the models to forecasting demand for four alternative technologies is discussed. Within the context of the input forecasts of population and gross domestic product, the models were found to produce reasonable results, with intuitively appropriate sensitivities. The results were also found to be adequate to guide initial assessments of feasibility