Synopses & Reviews
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.
Synopsis
1: Introduction.- 2: A new consistency test index for the data in the AHP/ANP.- 2.1 Basics of the AHP/ANP.- 2.1.1 The reciprocal pairwise comparison matrix.- 2.1.2 Basics of the AHP.- 2.1.3 Basics of the ANP.- 2.2 Consistency test issue in the AHP/ANP.- 2.2.1. Analysis of the consistency ratio (CR) method.- 2.2.2 The issues of consistency test in the AHP/ANP.- 2.3 The new consistency index--Maximum Eigenvalue Threshold for the AHP/ANP.- 2.3.1 The advantages of Maximum Eigenvalue Threshold for the AHP/ANP.- 2.4 The processes of data consistency test in the AHP/ANP.- 2.5. Illustrative example.- 3: IBMM for inconsistent data identification and adjustment in the AHP/ANP.- 3.1 The theorems of induced bias matrix model (IBMM) .- 3.1.1 The theoretical proofs of IBMM.- 3.2 IBMM for inconsistent data identification and adjustment.- 3.2.1 The basics of the inconsistency identification and adjustment method.- 3.2.2. The processes of inconsistency identification and adjustment method.- 3.2.3 Fast inconsistency identification and adjustment method.- 3.3. Illustrative examples.- 3.3.1 Illustrative examples for general inconsistency identification and adjustment method.- 3.3.2 Illustrative examples for fast inconsistency identification and adjustment method.- 4: IBMM for Missing Data Estimation.- 4.1 Basics of the IBMM for missing data estimation.- 4.2 The processes of estimating missing data by the IBMM.- 4.3 Proofs of the IBMM for IPCM in order three.- 4.4 Illustrative examples.- 4.4.1 Illustrative examples in order three.- 4.4.2 Illustrative examples in order four.- Chapter 5: IBMM for Questionnaire Design Improvement.- 5.1 Motivation of the research.- 5.2 The principles of improving the questionnaire design.- 5.3 Illustrative example.- Chapter 6: IBMM for rank reversal.- 6.1 Rank reversal issue in the AHP/ANP.- 6.2 Sensitivity analysis of rank reversal by the IBMM.- 6.3 Illustrative examples.- 7: Applications of IBMM.- 7.1 Task scheduling and resource allocation in cloud computing environment by the IBMM.- 7.1.1 Resource allocation in cloud computing.- 7.1.2 Task-oriented resource allocation in cloud computing.- 7.1.3 Illustrative example.- 7.2 Risk assessment and decision analysis by the IBMM.- 7.2.1 Background of risk assessment and decision analysis.- 7.2.2 Illustrative Examples.- 8. Induced Arithmetic Average Bias Matrix Model (IAABMM).- 8.1 The theorem of IAABMM.- 8.2 The inconsistency identification processes of IAABMM.- 8.3 The estimating formula of inconsistency adjustment.- 8.4. Illustrative Examples.- References.
Synopsis
This book examines issues of PCM, including consistency test, inconsistent data identification and adjustment, missing or uncertain data estimation, and sensitivity analysis of rank reversal. Proposes and demonstrates an induced bias matrix model (IBMM).
About the Author
Dr. Gang Kou is a professor of School of Management and Economics, University of Electronic Science and Technology of China and managing editor of International Journal of Information Technology & Decision Making. Previously, he was a research scientist in Thomson Co., R&D. He received his Ph.D. in Information Technology from the College of Information Science & Technology, Univ. of Nebraska at Omaha; got his Master degree in Dept of Computer Science, Univ. of Nebraska at Omaha; and B.S. degree in Department of Physics, Tsinghua University, Beijing, China. He has published more than eighty papers in various peer-reviewed journals and conferences. Gang Kou has been Keynote speaker/workshop chair in several international conferences. He co-chaired Data Mining contest on The Seventh IEEE International Conference on Data Mining 2007 and he is the Program Committee Co-Chair of the 20th International Conference on Multiple Criteria Decision Making (2009) and NCM 2009: 5th International Joint Conference on INC, ICM and IDC.
Table of Contents
1: Introduction.- 2: A new consistency test index for the data in the AHP/ANP.-