A Revised Weighted Fuzzy C-Means and Center of Gravity Algorithm for Probabilistic Demand and Customer Positions


Bayturk E., Esnaf S. , KÜÇÜKDENİZ T.

International Conference on Intelligent and Fuzzy Systems, INFUS 2020, İstanbul, Türkiye, 21 - 23 Temmuz 2020, ss.1523-1531 identifier

  • Cilt numarası:
  • Doi Numarası: 10.1007/978-3-030-51156-2_177
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.1523-1531

Özet

© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.This study proposes four probabilistic fuzzy c-means algorithms which include a probabilistic fuzzy c-means algorithm (Probabilistic FCM), a probabilistic revised weighted fuzzy c-means algorithm (Probabilistic RWFCM) and hybrid algorithms that combine these algorithms with the center of gravity methods for the un-capacitated planar multi-facility location problem when customer positions and customer demands are probabilistic with predetermined service level. The performance of proposed algorithms was tested with 13 data sets and compared with each other. Experimental results indicate that Probabilistic RWFCM-COG algorithm performs better than other compared algorithms in terms of cost minimization.