Multi criteria selection of components using the analytic hierarchy process

9Citations
Citations of this article
19Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The Analytic Hierarchy Process (AHP) has been successfully used in the past for the selection of components, as presented in case studies in the literature. In this paper, an empirical study using AHP to rank components is presented. The components used in the study are for data compression; each implements one of the Arithmetic Encoding (AREC), Huffman coding (HUFF), Burrows-Wheeler Transform (BWT), Fractal Image Encoding (FRAC), and Embedded Zero-Tree Wavelet Encoder (EZW) algorithms. The ranking is a semi-automated approach that is based on using rigorously collected data for the components' behavior; selection criteria include maximum memory usage, total response time, and security properties (e.g., data integrity). The results provide a clear indication that AHP is appropriate for the task of selecting components when several criteria must be considered. Though the study is limited to select components based on multiple non-functional criteria, the approach can be expanded to include multiple functional criteria. © Springer-Verlag Berlin Heidelberg 2006.

Cite

CITATION STYLE

APA

Cangussu, J. W., Cooper, K. C., & Wong, E. W. (2006). Multi criteria selection of components using the analytic hierarchy process. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4063 LNCS, pp. 67–81). Springer Verlag. https://doi.org/10.1007/11783565_5

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free