BENEFIT/COST ANALYSIS USING FUZZY CONCEPT

ABSTRACT

Two algorithms are proposed to perform benefit/cost analysts in a fuzzy environment. The first algorithm considers the fuzzy measure of benefit to cost ratio to select the optimal alternative group under the available funds. The second algorithm considers the fuzzy measure of incremental benefit to incremental cost ratio to choose the optimal investment alternative from several mutually exclusive investment alternatives. By using these algorithms, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision-making.

Additional information

Notes on contributors

MAO-JIUN WANG

GIN-SHUH LIANG is an Associate Professor of Department of Shipping and Transportation Management at National Taiwan Ocean University, Taiwan, Republic of China. He received his Ph.D. in Industrial Engineering from the National Tsing Hwa University at Taiwan in 1992. His research interestes include fuzzy set theory, ergonomics, information and management sciences, statistics and multiple criteria decision making.

GIN-SHUH LIANG

MAO-JIUN J. Wang is a Professor of Industrial Engineering at National Tsing Hwa University, Taiwan, R.O.C. Prior to that, he was an Assistant Professor of Industrial Engineering at Alfred University in Alfred, NY, and Associate Professor at NTHU. He received his Ph.D. in Industrial Engineering from State University of New York at Buffalo in 1986. His research interests include human factors/ergonomics, fuzzy set modeling and industrial inspection. He has published more than 30 journal papers in these areas.