An improved rough set approach to evaluate auto-mobility systems

Min Qu, Suihuai Yu, Dengkai Chen, Jianjie Chu, Zhixue Sun

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

To evaluate auto-mobility systems and find out which one can provide better environmental, social, economic benefits and better system performance, we improve a rough set approach proposed by [1] with the combination of Rough Analytic Hierarchy Process (R-AHP) and Rough Technique for Order Preference by Similarity to Ideal Solution (R-TOPSIS). There are three steps in the improved approach. In the first step, proper indicators are identified by means of literature review and expert interviews, and they are divided into two categories, benefit and cost. In the second step, weight for each indicator is determined by R-AHP. In the third step, different alternatives are compared and ranked by R-TOPSIS. A case study is provided to show the detailed procedure of the improved approach by comparing car-sharing, ride-sharing and car-owning. And sensitivity analysis experiments are conducted to figure out the effect of indicators on decision making process. We arrive at the conclusion that ride-sharing is the best auto-mobility option in most cases and indicators play a significant role in the evaluation of auto-mobility options.

Original languageEnglish
Pages (from-to)1339-1353
Number of pages15
JournalJournal of Intelligent and Fuzzy Systems
Volume33
Issue number3
DOIs
StatePublished - 2017

Keywords

  • auto-mobility
  • indicator
  • Rough analytic hierarchy process
  • rough technique for order preference by similarity to ideal solution

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