About this book
The positive reciprocal pairwise comparison matrix (PCM) is one of the key components which is used to quantify the qualitative and/or intangible attributes into measurable quantities. This book examines six understudied issues of PCM, i.e. consistency test, inconsistent data identification and adjustment, data collection, missing or uncertain data estimation, and sensitivity analysis of rank reversal.
The maximum eigenvalue threshold method is proposed as the new consistency index for the AHP/ANP. An induced bias matrix model (IBMM) is proposed to identify and adjust the inconsistent data, and estimate the missing or uncertain data.
Two applications of IBMM including risk assessment and decision analysis, task scheduling and resource allocation in cloud computing environment, are introduced to illustrate the proposed IBMM.
- DOI https://doi.org/10.1007/978-3-642-29213-2
- Copyright Information Springer-Verlag Berlin Heidelberg 2013
- Publisher Name Springer, Berlin, Heidelberg
- eBook Packages Business and Economics
- Print ISBN 978-3-642-29212-5
- Online ISBN 978-3-642-29213-2
- Series Print ISSN 2194-086X
- Series Online ISSN 2194-0878
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