Transportation investment project selection with fuzzy multiobjectives: Fid-Bau Portal

Transportation investment project selection with fuzzy multiobjectives

Tzeng, Gwo‐Hshiung / Teng, Junn‐Yuan

This paper proposes the application of fuzzy set theory to transportation investment planning. Performance of fuzziness after objectives are achieved will be subjectively judged by experts in related fields. The resource requirements can be predicted by experience rules or statistical techniques, while in this paper an issue of nonfuzziness will be considered. Within the fuzzy numbers of the achieved objective performance, this paper will find out the best crisp performance value by centroid rule, which is used to select transportation investment projects.

Since transportation investment planning cannot avoid dealing with issues of interrelationship among projects, this paper will consider three forms of investment projects: independence, complementarity and substitution. Complementary projects can enhance performance of objectives, while substitutive projects can only substitute, but not increase, objective performance. When this paper selects transportation investment projects, achievement of multiple objectives leads the way. It is hoped that the worst level of objectives can be achieved, and it thus belongs to “max‐min 0–1” multiobjective integer programming solutions. Spatially efficient algorithm is proposed in this paper so as to attain the approximate solutions, which, aside from ranking the selected investment projects, can easily perform sensitivity analysis. An example is presented to illustrate the method.