Transportation investment project selection using fuzzy multiobjective programming

Abstract This paper proposes the fuzzy multiobjective programming for the problem of transportation investment project selection (TIPS). The programming then uses the fuzzy spatial algorithm, which calculates the performance of objective achievement and the requirement of resource utilization as of fuzziness. Under a complex and uncertain decision-making environment, there exists a certain degree of interdependence among these transportation investment projects. This paper uses expert evaluation, and conducts, respectively, with the consensus of most of the experts, the decision on interdependency type (complementary and substitutive) and on the degree of fuzzy interdependence. In every iteration of the fuzzy spatial algorithm, the method of ranking fuzzy numbers must be used so as to obtain the ranking for selecting investment projects. This paper has modified the method provided by Kim and Park in order that the preference of most of the decision makers or experts can be overlooked, since the degree of optimism or pessimism can be demonstrated in the profitability of every investment project. In the end, this paper will employ a numerical example to illustrate the method forwarded.