Use of data envelopment analysis and clustering in multiple criteria optimization

Authors:
Marí/a Guadalupe Villarreal Marroquí/n;Matilde Luz Sá/nchez Peñ/a;Carlos E. Castro;José/ M. Castro;Mauricio Cabrera-Rí/os
Affiliations:
Graduate Program in Systems Engineering, Universidad Autó/noma de Nuevo Leó/n, San Nicolá/s de los Garza, Nuevo Leó/n 66450, Mé/xico;Graduate Program in Systems Engineering, Universidad Autó/noma de Nuevo Leó/n, San Nicolá/s de los Garza, Nuevo Leó/n 66450, Mé/xico;Graduate Program in Polymer Science and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;Department of Industrial, Welding & Systems Engineering, The Ohio State University, Columbus, OH 43210, USA;(Correspd. Tel.: +52 81 14920367/ Fax: +52 81 10523321/ mcabrera@mail.uanl.mx, mauricio.cabrera@gmail.com) Grad. Program in Sys. Eng., Universidad Autó/noma de Nuevo Leó/n, San Nicolá/ ...
Venue:
Intelligent Data Analysis
Year:
2008

Citing 5
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Journal of Integrated Design & Process Science - Manufacturing And Design

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Abstract

In manufacturing it is common to be required to simultaneously meet several performance measures with varying degrees of conflict among them. Such situation poses a multiple criteria optimization problem. Finding solutions to this kind of problems in an efficient manner is critical for industrial application. In this work, data clustering techniques are explored to make the solution process to multicriteria optimization problems efficient via Data Envelopment Analysis. The results of different clustering schemes are reported and conclusions are drawn from their evaluation.