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Clustering and Multifacility Location with Constraints via Distance Function Penalty Method and DC Programming

Nguyen Mau Nam (mnn3***at***pdx.edu)
Nguyen Thai An (thaian2784***at***gmail.com)
Sam Reynolds (ser6***at***pdx.edu)
Tuyen Tran (tuyen2***at***pdx.edu)

Abstract: This paper is a continuation of our effort in using mathematical optimization involving DC programming in clustering and multifacility location. We study a penalty method based on distance functions and apply it particularly to a number of problems in clustering and multifacility location in which the centers to be found must lie in some given set constraints. We also provide different numerical examples to test our method.

Keywords: Clustering, DC programming, Nesterov's smoothing techniques, k-mean algorithm

Category 1: Convex and Nonsmooth Optimization (Nonsmooth Optimization )


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Entry Submitted: 08/04/2017
Entry Accepted: 08/04/2017
Entry Last Modified: 05/02/2018

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