ESTIMATING WEIGHT Course: Special Topics in Remote Sensing & GIS Mirza Muhammad Waqar Contact: +92-21-34650765-79 EXT:2257 RG712.

Slides:



Advertisements
Similar presentations
Modellistica e Gestione dei Sistemi Ambientali A tool for multicriteria analysis: The Analytic Hierarchy Process Chiara Mocenni University of.
Advertisements

5/30/2014 Aosta, May 24th 2012 SESAMO: a decision support system for the Multi Criteria Analysis Fiorella GRASSO, Stefano MARAN (PP3) Project Final Meeting.
DECISION MODELING WITH Multi-Objective Decision Making
Multi‑Criteria Decision Making
Analytical Hierarchy Process (AHP) - by Saaty
1 1 © 2003 Thomson  /South-Western Slide Chapter 15 Multicriteria Decision Problems n Goal Programming n Goal Programming: Formulation and Graphical.
Life Cycle Assessment of Municipal Solid Waste Systems to Prioritize and Compare their Methods with Multi-Criteria Decision Making Hamid Reza Feili *,
1 1 Slide Chapter 10 Multicriteria Decision Making n A Scoring Model for Job Selection n Spreadsheet Solution of the Job Selection Scoring Model n The.
Analytic Hierarchy Process Multiple-criteria decision-making Real world decision problems –multiple, diverse criteria –qualitative as well as quantitative.
MIS 463 Analytic Hierarchy Process. 2 The Analytic Hierarchy Process (AHP) It is popular and widely used method for multi-criteria decision making. Allows.
Lecture 08 Analytic Hierarchy Process (Module 1)
1 Critical Success Factors and Organizational Performance Prepared by: Niemann, Lahlou, Zertani & Pflug Lecturer: Ihsan Yüksel.
Introduction to Management Science
Copyright © 2006 Pearson Education Canada Inc Course Arrangement !!! Nov. 22,Tuesday Last Class Nov. 23,WednesdayQuiz 5 Nov. 25, FridayTutorial 5.
1 1 Slide © 2005 Thomson/South-Western EMGT 501 HW Solutions Problem Problem
Multi Criteria Decision Modeling Preference Ranking The Analytical Hierarchy Process.
I’M THINKING ABOUT BUYING A CAR BUT WHICH ONE DO I CHOOSE? WHICH ONE IS BEST FOR ME??
Assignment of Weights Other methods, besides arbitrary, for weight assignment exist There are both direct and indirect weight elicitation techniques Source:
MENENTUKAN LOKASI PABRIK YANG IDEAL MENGGUNAKAN AHP PERTEMUAN 12.
Introduction to Management Science
On Fairness, Optimizing Replica Selection in Data Grids Husni Hamad E. AL-Mistarihi and Chan Huah Yong IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS,
1 1 Slide © 2005 Thomson/South-Western EMGT 501 HW Solutions Chapter 14 - SELF TEST 20.
9-1 Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Multicriteria Decision Making Chapter 9.
Multicriteria Decision Making
9-1 Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Multicriteria Decision Making Chapter 9.
Presented by Johanna Lind and Anna Schurba Facility Location Planning using the Analytic Hierarchy Process Specialisation Seminar „Facility Location Planning“
1 1 Slide © 2001 South-Western College Publishing/Thomson Learning Anderson Sweeney Williams Anderson Sweeney Williams Slides Prepared by JOHN LOUCKS QUANTITATIVE.
Analytical Hierarchy Process ( AHP )
Quantitative Analysis for Management Multifactor Evaluation Process and Analytic Hierarchy Process Dr. Mohammad T. Isaai Graduate School of Management.
1 1 Slide © 2004 Thomson/South-Western Chapter 17 Multicriteria Decisions n Goal Programming n Goal Programming: Formulation and Graphical Solution and.
Spreadsheet Modeling and Decision Analysis, 3e, by Cliff Ragsdale. © 2001 South-Western/Thomson Learning Multicriteria Decision Making u Decision.
The Analytic Hierarchy Process (AHP) is a mathematical theory for measurement and decision making that was developed by Dr. Thomas L. Saaty during the.
Decision Technology Modeling, Software and Applications Matthew J. Liberatore Robert L. Nydick John Wiley & Sons, Inc.
Multi-Criteria Decision Making by: Mehrdad ghafoori Saber seyyed ali
1 Chapter 16 The Analytic Hierarchy Process. 2 The analytic hierarchy process (AHP), which was developed by Thomas Saaty when he was acting as an adviser.
Recap: How the Process Works (1) Determine the weights. The weights can be absolute or relative. Weights encompass two parts -- the quantitative weight.
Chapter 9 - Multicriteria Decision Making 1 Chapter 9 Multicriteria Decision Making Introduction to Management Science 8th Edition by Bernard W. Taylor.
Multi Criteria Decision Making
MAINTENANCE STRATEGY SELECTION BASED ON HYBRID AHP-GP MODEL SUZANA SAVIĆ GORAN JANAĆKOVIĆ MIOMIR STANKOVIĆ University of Niš, Faculty of Occupational Safety.
Agenda for This Week Wednesday, April 27 AHP Friday, April 29 AHP Monday, May 2 Exam 2.
THE ANALYTIC HIERARCHY PROCESS CAR PURCHASE EXAMPLE.
Analytic Hierarchy Process. 2 The Analytic Hierarchy Process (AHP) Founded by Saaty in It is a popular and widely used method for multi-criteria.
Multi-Criteria Analysis - preference weighting. Defining weights for criteria Purpose: to express the importance of each criterion relative to other criteria.
To accompany Quantitative Analysis for Management, 9e \by Render/Stair/Hanna M1-1 © 2006 by Prentice Hall, Inc. Upper Saddle River, NJ Analytic Hierarchy.
BUSINESS PERFORMANCE MANAGEMENT
Analytic Hierarchy Process (AHP)
Fitness Cases Are input-output pairs describing the output a program should produce given the particular input value. The fitness of an individual is usually.
Model Calibration and Weighting Avoid areas of… High Housing Density Far from Roads In or Near Sensitive Areas High Visual Exposure …what is “high” housing.
Applied Mathematics 1 Applications of the Multi-Weighted Scoring Model and the Analytical Hierarchy Process for the Appraisal and Evaluation of Suppliers.
Analytic Hierarchy Process (Contd)
Constructing the PAHP-based Decision Support System by Considering the Ambiguity in Decision Making Norihiro Saikawa Department of Computer and Information.
To Accompany Russell and Taylor, Operations Management, 4th Edition,  2003 Prentice-Hall, Inc. All rights reserved. Supplement S7 Supplier Selection.
ON ELICITATION TECHNIQUES OF NEAR-CONSISTENT PAIRWISE COMPARISON MATRICES József Temesi Department of Operations Research Corvinus University of Budapest,
MCE: Eigen Values Calculations from Pair Wise Comparisons. Addition to Exercise 2-8.
This Briefing is: UNCLASSIFIED Aha! Analytics 2278 Baldwin Drive Phone: (937) , FAX: (866) An Overview of the Analytic Hierarchy Process.
Reality of Highway Construction Equipment in Palestine
Supplement S7 Supplier Selection.
MULTI CRITERIA DECISION MAKING - APPLICATIONS IN PROJECT MANAGEMENT
Analytic Hierarchy Process (AHP)
A Scoring Model for Job Selection
ANALYTIC HIERARCHY PROCESS (AHP)
Decision Matrices Business Economics.
Analytic Hierarchy Process Prepared by Lee Revere and John Large
Analytical Hierarchy Process
Analytic Hierarchy Process (AHP)
Slides by John Loucks St. Edward’s University.
Agenda for This Week Monday, April 25 AHP Wednesday, April 27
Multicriteria Decision Making
IME634: Management Decision Analysis
AHP (Analytic Hierarchy process)
Presentation transcript:

ESTIMATING WEIGHT Course: Special Topics in Remote Sensing & GIS Mirza Muhammad Waqar Contact: EXT:2257 RG712

Estimating Weights  A weight can be defined as a value assigned to an evaluation criterion that indicates its importance relative to other criteria under consideration.  The larger the weight, the more important is the criterion in the overall utility.  Assigning weights of importance to evaluation criteria accounts for: 1. Changes in the range of variation for each evaluation criterion 2. The different degrees of importance being attached to these ranges of variation.

Ranking Method  The simplest method for assessing the importance of weights is to arrange them in rank order in the order of the decision maker’s preference.  Straight ranking 1 most important,2,3…n least important  Inverse ranking 1: least important, 2,3…n most important  Once the ranking established for a set of criteria, generate numerical weights from rank‐order information

Ranking Method P = 0 results in equal weights to all the criteria P = 1 results in rank sum weight

Site Selection using Ranking Method

Rating Method  The rating methods require the decision maker to estimate weights on the basis of a predetermined scale.  i.e. 0 to 100  0 indicted that the criterion can be ignored  100 means only one criterion need to be considered.

1.Point Allocation Method  50 points to the cost of establishing the plant. (W: 0.5)  30 points to accessibility to the transportation. (W: 0.3)  20 points to the availability of water. (W: 0.2)  Sum= 0 (ignore) location Sum=100 Select with confidence

2.Ratio Estimation Procedure  It starts by assigning an arbitrary weight to the most important criterion, as identified by one of the ranking methods.  A score of 100 is assigned to the most important criterion.  Proportionately smaller wrights are then given to criteria lower in the order.  The procedure is continued until a score is assigned to the least important criterion which shall then be taken as an anchor point for calculating the ratios.  Score of each criterion is divided by the score of the least important criterion W j /W * where W j is the score for the j th criterion and W * is lowest score.

Site Selection using Rating Method

Pair‐wise Comparison Methods  Developed by Saatay (1980) in the context of AHP (Analytic Hierarchy Process)  This method involves pair‐wise comparisons to create a ratio matrix.  It takes pair‐wise comparisons as input and produces the relative weights as output. 1. Development of the pair‐wise comparison matrix 2. Computation of the criterion weights 3. Estimation of the consistency ratio

Scale for Pair‐wise Comparison

Example: Site Suitability Analysis  Parameters: 1. Price 2. Slope 3. View  Price is moderately to strongly preferred over slope  Price is very strongly preferred over view  Slope is strongly preferred over view

Step1: Development of Pairwise Comparison Matrix

Step2: Computation of the Criterion Weights  This step involves following operations: 1. Sum the values in each column of the pair-wise comparison matrix. 2. Divide each element in the matrix by its column total 3. Compute the average of elements in each row of the normalized matrix.

Step2: Computation of the Criterion Weights

Step3: Estimation of the Consistency Ratio  This step involves following operations:  Determine the weighted sum vector by multiplying the criterion weights with the values of the original pairwise comparison matrix and finally sum these values over rows.  Determine the consistency vector by dividing the weighted sum vector by the criterion weights.

Step3: Estimation of the Consistency Ratio

Step3: Estimation of the Consistency ratio  Computation of Lambda λ : λ = ( ) / 3 =  λ should always be greater than or equal to the number of criterion to be considered.  λ = n (if the pair wise comparison matrix is a consistent matrix)

Step3: Estimation of the Consistency ratio  Computation of CI (Consistency Index) :  CI= (λ‐n) / (n-1) = (3.128‐3) / (3-1) =  Computation of CR (Consistency Ratio) :  CR= CI / RI = / 0.58 =  Where RI is the random index provided by Saaty and it depends on the number of criterion (n).

Random Inconsistency Index RI  If CR<0.10 the ratio indicates a reasonable level of consistency.  If CR>0.10 the ratio indicates an inconsistent judgment and the relative criterion pair wise comparison matrix needs reconsideration and the whole process must be repeated.

Questions & Discussion