A multi-criteria route planning model based on fuzzy preference degrees of stops


Nasibov E., Diker A. C., Nasibov E.

APPLIED SOFT COMPUTING, cilt.49, ss.13-26, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 49
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1016/j.asoc.2016.07.052
  • Dergi Adı: APPLIED SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.13-26
  • Anahtar Kelimeler: Fuzzy modeling, Route planning, Preference degree, Heuristic algorithm, INFORMATION, AGGREGATION, ALGORITHM, NETWORK
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Integrated utilization of new technologies such as smart phones, tablet devices, and satellite maps has entered our daily lives recently. Nevertheless, many new applications are being developed mostly based on these technologies. The optimal route planning, which makes use of the public transport network structure between any selected origin and destination points, is one of the interesting applications among them. Route planning applications used today mostly focus on the aspects such that passengers use nearest stops around origin and destination geographical points, or use set of stops around these points within some walking radius. In these applications, which work on the classical (crisp) logic base, all stops on the walking distance have the same preference degree. However, in this study a novel fuzzy model is proposed which also takes into account preferences such as the stop's activity, and count of transit lines passing through the stop besides the walking distance. Using all these three preferences, aggregated fuzzy preference degrees of stops are calculated. The "optimum" routes between any origin and destination pair are constructed using feasible transfer points, which are chosen among the alternatives having the highest preference degrees overall. Fuzzy neighborhood relations such as "stop-stop", "stop-line", and line-line" are introduced in order to employ in preference degree evaluations.