Proposing a new approach to the selection of material portfolio using a combination of data mining and optimisation methods

Farshad Faezy Razi and Hamed Sarkari

International Journal of Operational Research, 2019, vol. 36, issue 2, 151-169

Abstract: The present paper aims to provide a new framework for the selection of a portfolio of materials. This paper shows that, compared with the traditional methods in the selection of materials, how the new materials are analysed based on new ideas. The case study is materials required for production of tile glaze in both traditional and modern methods. Modelling in this study was done based on mathematical description approach. The results of execution of feature selection algorithm revealed that important factors in the selection of glaze for production of tile in both traditional and modern methods include cracking, self-cleaning, uniformity, water absorption, and market potential. In addition, the results of K-means algorithm showed that all the materials of choice for production of tile glaze are not placed in a single cluster. Therefore, each cluster should be evaluated separately. Unlike the classical approaches to the selection of materials, in the new approach, candidates for the selection of tile glaze are firstly clustered by K-means algorithm. Each cluster is independently ranked using free disposal hull model. Free disposal hull is a mathematical programming model based on data envelopment analysis. The final optimised portfolio of materials was determined using the genetic algorithm.

Keywords: material selection; feature selection algorithm; K-means algorithm; DEA-FDH; genetic algorithm. (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=102408 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:36:y:2019:i:2:p:151-169

Access Statistics for this article

More articles in International Journal of Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().