An Optimal Investment Scheduling Framework for Intelligent Transportation Systems Architecture
Transportation planning in general, and planning for intelligent transportation systems (ITSs) in particular, are notable for multiple goals and for multiple constituencies. A review of the current literature offers several ITS investment evaluation methods that provide frameworks for the quantification of risks and benefits. Nevertheless, the traditional selection methods overemphasize quantitative and economic analysis and often neglect to consider qualitative and noneconomic data in the formal selection process. Furthermore, crisp data are fundamentally indispensable in traditional ITS investment selection methods. However, the data in real-world problems are often imprecise or ambiguous. In this article, we propose a novel fuzzy group multi-criteria framework for ITS investment evaluation and selection that takes into consideration (1) the qualitative and quantitative criteria and their respective value judgments; (2) the verbal expressions and linguistic variables for qualitative judgments which lead to ambiguity in the decision process; and (3) imprecise or vague judgments. First, we use fuzzy TOPSIS to calculate the fuzzy risk values with each ITS architecture subsystem. Next, we use fuzzy ROA to calculate the fuzzy real option values of the ITS subsystems. Last, we determine the optimal investment schedule for the ITS subsystems by considering the risk and option values as the coefficients of the objective functions in a group multi-objective decision-making model.
Zandi, Faramak and Tavana, Madjid, "An Optimal Investment Scheduling Framework for Intelligent Transportation Systems Architecture" (2011). Business Systems and Analytics Faculty Work. 270.