Analytic Hierarchy Process (AHP)

Slides:



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

DECISION MODELING WITH Multi-Objective Decision Making
Multi‑Criteria Decision Making
Eigenvectors and Decision Making Analytic Hierarchy Process (AHP) Positive Symmetrically Reciprocal Matrices (PSRMs) and Transitive PSRMs Estimation methods.
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.
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)
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??
THE ANALYTIC HIERARCHY PROCESS. Analytic Hierarchy Process ► Analytic Hierarchy Process (AHP) is a multicriteria decision-making system. ► AHP was developed.
MENENTUKAN LOKASI PABRIK YANG IDEAL MENGGUNAKAN AHP PERTEMUAN 12.
Economics 2301 Matrices Lecture 13.
Introduction to Management Science
1 Multi-Criteria Decision Making MCDM Approaches.
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
1 1.1 © 2012 Pearson Education, Inc. Linear Equations in Linear Algebra SYSTEMS OF LINEAR EQUATIONS.
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“
Systems and Matrices (Chapter5)
Analytical Hierarchy Process ( AHP )
tables Objectives: By the end of class today I will:
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.
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.
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
The Analytic Network Process Decision Making with Dependence and Feedback.
« Investment scenarios and regional factors in the solar energy sector » Dr. Nikolaos Apostolopoulos The Macrojournals /MacroTrends Conference: New York.
Applied Mathematics 1 Applications of the Multi-Weighted Scoring Model and the Analytical Hierarchy Process for the Appraisal and Evaluation of Suppliers.
SECTION 2 BINARY OPERATIONS Definition: A binary operation  on a set S is a function mapping S X S into S. For each (a, b)  S X S, we will denote the.
Analytic Hierarchy Process Do your decision conferences turn out like this?
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.
ESTIMATING WEIGHT Course: Special Topics in Remote Sensing & GIS Mirza Muhammad Waqar Contact: EXT:2257 RG712.
© 2010 Pearson Prentice Hall. All rights reserved. CHAPTER 13 Mathematical Systems.
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.
Analytic Hierarchy Process Multiple-criteria decision-making Real world decision problems –multiple, diverse criteria –qualitative as well as quantitative.
Tell whether the matrix is equal to the fundraiser matrix. Explain.
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)
Analytic Hierarchy Process Prepared by Lee Revere and John Large
Analytic Hierarchy Process (AHP)
Quantitative Techniques for Decision Making-4 (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
Presentation transcript:

Analytic Hierarchy Process (AHP) BasmahALQadheeb-2012

Analytic Hierarchy Process (AHP) Is one of Multi Criteria decision making method that was originally developed by Prof. Thomas L. Saaty. Is an excellent modeling structure for representing multicriteria (multiple goals, multiple objectives) problems—with sets of criteria and alternatives (choices)- commonly found in business environments. In short, it is a method to derive ratio scales from paired comparisons BasmahALQadheeb-2012

level0 level1 level2 BasmahALQadheeb-2012

Level 0 is the goal of the analysis Level 0 is the goal of the analysis. Level 1 is multi criteria that consist of several factors . Level 2 in is the alternative choices. The input of AHP can be obtained from actual measurement such as price, weight etc., or from subjective opinion such as satisfaction feelings and preference. AHP allow some small inconsistency in judgment because human is not always consistent. BasmahALQadheeb-2012

Pair-Wise Comparison Now let me explain what paired comparison is Suppose we have two fruits Apple and Banana. I would like to ask you, which fruit you like better than the other and how much you like it in comparison with the other BasmahALQadheeb-2012

. Let us make a relative scale to measure how much you like the fruit on the left (Apple) compared to the fruit on the right (Banana). For instance I strongly favor banana to apple then I give mark like this Researchers have confirmed the 9-unit scale as a reasonable basis for discriminating between the preferences for two items. BasmahALQadheeb-2012

Now suppose you have three choices of fruits Now suppose you have three choices of fruits. Then the pair wise comparison goes as the following You may observe that the number of comparisons is a combination of the number of things to be compared. Since we have 3 objects (Apple, Banana and Cheery), we have 3 comparisons. BasmahALQadheeb-2012

Table below shows the number of comparisons. BasmahALQadheeb-2012

Example of Analytic Hierarchy Process For example John has 3 kinds of fruits to be compared BasmahALQadheeb-2012

In level 1 you will have one comparison matrix corresponds to pair-wise comparisons between 3 factors with respect to the goal. Thus, the comparison matrix of level 1 has size of 3 by 3. BasmahALQadheeb-2012

Making Comparison Matrix We have 3 by 3 matrix The diagonal elements of the matrix are always 1 and we only need to fill up the upper triangular matrix. How to fill up the upper triangular matrix is using the following rules: If the judgment value is on the left side of 1, we put the actual judgment value. If the judgment value is on the right side of 1, we put the reciprocal value . BasmahALQadheeb-2012

John made subjective judgment on which fruit he likes best, like the following BasmahALQadheeb-2012

Comparing apple and banana, John slightly favor banana, thus we put 1/3 in the row 1 column 2 of the matrix. Comparing Apple and Cherry, John strongly likes apple, thus we put actual judgment 5 on the first row, last column of the matrix. Comparing banana and cherry, banana is dominant. Thus we put his actual judgment on the second row, last column of the matrix. Then based on his preference values above, we have a reciprocal matrix like this BasmahALQadheeb-2012

BasmahALQadheeb-2012

Priority Vector The priority vector shows relative weights among the things that we compare. Suppose we have 3 by 3 reciprocal matrix from paired comparison BasmahALQadheeb-2012

We sum each column of the reciprocal matrix to get BasmahALQadheeb-2012

Then we divide each element of the matrix with the sum of its column, we have normalized relative weight. The sum of each column is 1. BasmahALQadheeb-2012

The normalized principal Eigen vector can be obtained by averaging across the rows The normalized principal Eigen vector is also called priority vector BasmahALQadheeb-2012

In our example above, Apple is 28. 28%, Banana is 64 In our example above, Apple is 28.28%, Banana is 64.34% and Cherry is 7.38%. John most preferable fruit is Banana, followed by Apple and Cheery BasmahALQadheeb-2012