Gang Kou, Daji Ergu, Yi Peng, Yong Shi

Data Processing for the AHP/ANP (eBook, PDF)

• Format: PDF

Produktbeschreibung

Produktdetails

• Verlag: Springer Berlin
• Erscheinungstermin: 3. September 2012
• Englisch
• ISBN-13: 9783642292132
• Artikelnr.: 37799443

Autorenporträt

Inhaltsangabe

---

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 resourceallocation 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.

Rezensionen

From the reviews:

"Data Processing for the AHP/ANP focuses on the induced bias matrix model and its application in the AHP / ANP. ... this book might interest ... researchers in the AHP / ANP or, more generally, in decision-making procedures. ... The book is well organized, introduces readers to the main methodological problems in applications of AHP / ANP models, and suggests how to use the IBMM to solve them." (Josef Jablonsky, Interfaces, Vol. 43 (5), September-October, 2013)