Analysis of Ranking Continuous Fuzzy Random Information —A Case Study of Traffic Assignment Problem in Tamsui Area

• Main Authors: ChengHuo Lin, 林政和
• Other Authors: ShihHsien Liu
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/66967727452786477195

碩士 === 淡江大學 === 運輸管理學系 === 91 === Although, the fuzzy theorem is in blossom today, a lot of research papers named fuzzy number in transportation area remain in the use of stochastic logit approach. These studies overlook the differences between fuzzy and stochastic in nature. Therefore, some problem is over-simplified and not really solved in realistic uncertain circumstances. The traffic environment is complicated and highly stochastic due to uncertain and changing key factors. When facing several alternatives, decision makers based on their preferences usually make choice to maximize their benefits, all of which in a macro scale displays uncertain outcomes. In the past decade, the stochastic model, such as logit model or probit model, is the exclusive tool to solve the uncertain problem in the field of transportation. While traffic information is both fuzzy and stochastic, there is not any theoretical way to interpret this situation right now. In this study, we propose a new approach to comparing fuzzy numbers motivated by a probabilitic view of the underling uncertainty. We discuss the effect of decision attitude and show that this approach is particularly useful for aiding decision makers while information is fuzzy. Finally, we try to use this new approach in traffic assignment problem in Tamsui Area.