The main purpose of this research was to solve a real-world, multi-criteria, revitalization strategies project selection problem for the historic Alishan Forest Railway in Taiwan by using fuzzy Delphi, analytic network process (ANP), and zero-one goal programming (ZOGP). This required identifying the most cost-beneficial projects for maximizing the net benefit to the public and allocating resources most efficiently. To evaluate different revitalization strategies, we used a hierarchical network model based on various factors, and we present the interactions of those factors. The proposed ANP model consists of a control hierarchy and a network of connections between the clusters of alternatives, actors, and criteria. The strategic criteria were included into the model to rate benefits (B), opportunities (O), costs (C), and risks (R). A synthesis of alternatives was finally obtained using rated BOCR. In this paper, we suggest an improved methodology, one that uses an integrated approach and reflects the interdependencies between the evaluation criteria and candidate projects. The management of the Alishan Forest Railway has implemented the processing system proposed by this research and suggested to the government the best alternative strategies.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence