Transportation projects selection process using fuzzy sets theory

Government transportation agencies are faced with the problem of efficiently selecting a subset of transportation projects for implementation. This selection process is based on multiple objectives which are often measured in incommensurable units. Usually, the problem is treated by neglecting or biasing the qualitative characteristics of the various projects. Moreover, the usual selection methods cannot deal effectively with the decision makers’ preferences or vagueness. Fuzzy sets theory is able to cope with inexact information, and therefore is believed to be an appropriate tool for use in the projects’ selection process. This work presents an efficient technique for the selection of transportation projects using fuzzy sets theory. The selection procedure is a multiple objectives process, and projects are rated both on a quantitative and qualitative basis, using linguistic variables. In order to describe appropriately a given transportation policy, both fuzzy weighted average and noncompensatory fuzzy decision rules are used in the proposed approach. In addition, this work contains a case study of a selection process of interurban road projects in Israel. The results of the proposed method, obtained by a fuzzy expert system, are compared with the results obtained by an ordinary crisp process.