The purpose of this paper is to propose hybrid revised weighted fuzzy c-means (RWFCM) clustering and Nelder–Mead (NM) simplex algorithm, called as RWFCM-NM, for generalized multisource Weber problem (MWP).
Although the RWFCM claims that there is no obligation to sequentially use different methods together, NM’s local search advantage is investigated and performance of the proposed hybrid algorithm for generalized MWP is tested on well-known research data sets.
Test results state the outstanding performance of new hybrid RWFCM and NM simplex algorithm in terms of cost minimization and CPU times.
Proposed approach achieves better results in continuous facility location problems.
Conflict of interest: the authors declare that they have no conflict of interest.
Compliance with ethical standards: this paper does not contain any studies with human participants or animals performed by any of the authors.
Kucukdeniz, T. and Esnaf, S. (2018), "Hybrid revised weighted fuzzy c-means clustering with Nelder-Mead simplex algorithm for generalized multisource Weber problem", Journal of Enterprise Information Management, Vol. 31 No. 6, pp. 908-924. https://doi.org/10.1108/JEIM-01-2018-0002Download as .RIS
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