Loading presentation...

Present Remotely

Send the link below via email or IM

Copy

Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.

DeleteCancel

Make your likes visible on Facebook?

Connect your Facebook account to Prezi and let your likes appear on your timeline.
You can change this under Settings & Account at any time.

No, thanks

DECISION MAKING ITU

No description
by

eren gökgür

on 29 April 2013

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of DECISION MAKING ITU

Problem solving is a set of activities designed to analyze
a situation systematically and generate, implement, and
evaluate solutions.

Decision making is a mechanism for making choices at
each step of the problem-solving process.

Decision making is part of problem solving and occurs at every
step of the problem-solving process. AHP
ANP definition of decision making Decision Making Steps & Stages EVERYDAY TECHNİQUES DECISİON TREES BENEFİT Based on mathematics and psychology, it was developed by Thomas L. Saaty in the 1970s and has been extensively studied since then.

AHP is a effective decision making method especially when subjectivity exists and it is very suitable to solve problems where the decision criteria can be organized in a hierarchical way into sub-criteria (Tuzmen and Sipahi, 2011).
The question “Which one do we choose?” or “Which one is the best ?” by selecting the best alternative that matches all of the decision maker’s criteria. When people faced with a complex problem in order to understand the problem better they must break down the problem into its smaller constituent parts and construct a hierarchical model to represent it. Why Hierarchy? • STATE THE OBJECTIVE:
– Select the best boat
• DEFINE THE CRITERIA:
– Cost , motor power , comfort
• PICK THE ALTERNATIVES:
– Broadwater , C&H , Picobuy An important part of the process is to accomplish these three steps Standard Preference Table

Because the standard preference table has been determined by experienced researchers in AHP to be a reasonable basis for comparing two alternatives. Why not make up your own preference table ?
Using pairwise comparisons, the relative importance of one criterion over another can be expressed.


Cost is 2 times as important as reliability

Comfort is 4 times as important as style Pairwise Comparisons
C & H Broadwater Picobuy

C & H 1 1/3 6
Broadwater 3 1 7
Picobuy 1/6 1/7 1
Pairwise Comparison Matrix for Cost
C & H Broadwater Picobuy

C & H 6/25 7/31 6/14
Broadwater 18/25 21/31 7/14
Picobuy 1/25 3/31 1/14 Divide each entry in the pairwise comparison matrix by its corresponding column sum. For example, for C & H the column sum = 1 + 3 + 1/6 = 25/6. This gives:
Normalized Matrix for Cost Average the above results to get lmax.
lmax = (3.097 + 3.179 + 3.029)/3 = 3.102
Compute the consistence index, CI, for two terms by:
CI = (lmax - n)/(n - 1) = (3.102 - 3)/2 = .051
Compute the consistency ratio, CR, by CI/RI, where RI = .58 for 3 factors:
CR = CI/RI = .051/.58 = .088

Since the consistency ratio, CR, is less than .10, this is well within the acceptable range for consistency.
Checking Consistency The priority vector is determined by averaging the row entries in the normalized matrix. Converting to decimals we get:

C & H: ( 6/25 + 7/31 + 6/14)/3 = 0.298
Broadwater: (18/25 + 21/31 + 7/14)/3 = 0.632
Picobuy: ( 1/25 + 3/31 + 1/14)/3 = 0.069
Priority Vector For Cost Multiply each column of the pairwise comparison matrix by its priority:
1 1/3 6 .923
.298 3 + .632 1 + .069 7 = 2.009
1/6 1/7 1 .209

Divide these number by their priorities to get:
.923/.298 = 3.097
2.009/.632 = 3.179
.209/.069 = 3.029
Checking Consistency Average the above results to get lmax.
lmax = (3.097 + 3.179 + 3.029)/3 = 3.102
Compute the consistence index, CI, for two terms by:
CI = (lmax - n)/(n - 1) = (3.102 - 3)/2 = .051
Compute the consistency ratio, CR, by CI/RI, where RI = .58 for 3 factors:
CR = CI/RI = .051/.58 = .088

Since the consistency ratio, CR, is less than .10, this is well within the acceptable range for consistency.
Checking Consistency The Analytic Network Process is a more general form of the Analytic Hierarchy Process used in multi-criteria decision analysis.

ANP is a methodology that allows groups or individuals to deal with the interconnections (dependence and feedback) between factors of complex structure in decision making process
Analytic Network Process Many decisions problems cannot be structured hierarchically because they involve the interaction and dependence of higher level elements in a hierarchy on lower level elements (Saaty and Özdemir, 2005). While the AHP represents a framework with a uni-directional hierarchical AHP relationship, the ANP allows for complex interrelationships among decision levels and attributes (Yüksel and Dağdeviren, 2007). Structural Difference between Hierarchy (a) and Network (b) Processes C & H
Broadwater
Picobuy C & H
Broadwater
Picobuy C & H
Broadwater
Picobuy COMFORT MOTOR POWER COST SELECT A NEW GADGET THIS INFORMATION IS THEN ARRANGED
IN A HIERARCHICAL TREE COST MOTOR
POWER COMFORT C & H
BROADWATER
PICOBUY C & H
BROADWATER
PICOBUY C & H
BROADWATER
PICOBUY VOCATIONAL TRAINING COLLAGE PREP MUSIC CLASSES LISTENING FRIENDS SCHOOL LIFE A task is to sew a patch onto a pair of jeans. The best needle to do the threading is a 4 inch long needle with a 3 millimeter eye. This needle is hidden in a haystack along with 1000 other needles varying in size from 1 inch to 6 inches.

Satisficing claims that the first needle that can sew on the patch is the one that should be used. Spending time searching for that one specific needle in the haystack is a waste of energy and resources. Example This is a commonly recognized decision making technique used in everyday life :

coin flipping, cutting a deck of playing cards, finding a quotation in a holy book, consulting the Magic 8-ball, rolling a die, and other random or coincidence methods;
astrology, augury, fortune cookies, prayer, tarot cards, revelation, Methods of divination or other forms of divination or oracular device. Flipism and Divination Satisficing is a decision-making strategy that attempts to meet an acceptability threshold.

This is contrasted with optimal decision-making, an approach that specifically attempts to find the best option available.

The word satisfice was given its current meaning by Herbert A. Simon Satisficing (satisfy and suffice) Choosing the alternative with the highest probability-weighted utility for each alternative

Simple prioritization has also 4 steps such as :
1- Identify the Projects
2- Assess the Business Value
3- Assess the “Do- Ability”
4- Plot the Results and Make Your Choices Simple Prioritization Everyday Techniques Simple Prioritization Listing the advantages and disadvantages of each option
Popularized by Plato and Benjamin Franklin
Contrast the costs and benefits of all alternatives
It also called Rational decision making. Pros and Cons Pros and cons
Simple Prioritization
Satisficing
Elimination by Aspects
Filipism
Some divination
Opportunity cost
Political
Bureaucratic
Fuzzy Logic
Neural Network App. Everyday Techniques in Decision Making Flipism is a normative decision theory in a sense that it prescribes how decisions should be made.

Flipism shows remarkable ability to make right conclusions without any information Flipism and Divination In decision making, satisficing explains the tendency to select the first option that meets a given need or select the option that seems to address most needs rather than the “optimal” solution. Satisficing (satisfy and suffice) Fuzzy logic allows for approximate values and inferences as well as incomplete or ambiguous data (fuzzy data) as opposed to only relying on crisp data (binary yes/no choices). FUZZY LOGIC Fuzzy logic is a form of many-valued logic or probabilistic logic; it deals with reasoning that is approximate rather than fixed and exact. Degrees of truth

In standard mathematics unambiguously true or false.
For instance, the proposition zero belongs to the set { 0 } is regarded as simply false; while the proposition one belongs to the set { 1 } is regarded as simply true. However, some mathematicians, computer scientists, and philosophers have been attracted to the idea that a proposition might be more or less true, rather than simply true or simply false. Mathematics, this idea can be developed in terms of fuzzy logic. In computer science, it has found application in artificial intelligence. In philosophy, the idea has proved particularly appealing in the case of vagueness.

Degrees of truth is an important concept in law.Both degrees of truth and probabilities range between 0 and 1 and hence may seem similar at first. For example, let a 100 ml glass contain 30 ml of water. Then we may consider two concepts: Empty and Full. The meaning of each of them can be represented by a certain fuzzy set. Then one might define the glass as being 0.7 empty and 0.3 full.

Note that the concept of emptiness would be subjective and thus would depend on the observer or designer. DEGREES OF TRUTH
A basic application might characterize a continuous variable.

For instance, a temperature measurement for anti-lock brakes might have several separate membership functions defining particular temperature ranges needed to control the brakes properly.

Each function maps the same temperature value to a truth value in the 0 to 1 range. These truth values can then be used to determine how the brakes should be controlled. Artificial neural networks are composed of interconnecting artificial neurons for solving artificial intelligence problems without creating a model of a real system.

Neural network algorithms abstract away the biological complexity by focusing on the most important information. The goal of artificial neural networks is good, or human-like, predictive ability. NEURAL NETWORK APP. Artificial intelligence and cognitive modeling try to simulate some properties of biological neural networks. While similar in their techniques, the former has the aim of solving particular tasks, while the latter aims to build mathematical models of biological neural systems. APPLICATIONS OF NEURAL NETWORK Function approximation, or regression analysis, including time series prediction and modeling.

Classification, including pattern and sequence recognition, novelty detection and sequential decision making.

Data processing, including filtering, clustering, blind signal separation and compression. ANALYTIC NETWORK PROCESS Why Hierarchy ? What is Decision Making? The process of deciding about something important, especially in a group of people or in an organization. What is Decision Making? continuous and dynamic activity vital importance in the functioning of an organization requires solid scientific knowledge skills and experience with mental maturity Further, decision making process can be regarded as check and balance system that keeps the organisation growing both in vertical and linear directions. In a management setting, decision cannot be taken abruptly. It should follow the steps such as Defining the problem Gathering information and collecting data Developing a the options Plan and execute Choosing best possible option Take follow up action Every manager takes hundreds and hundreds of decisions subconsciously or consciously making it as the key component in the role of a manager Decisions are made at every level of management to ensure organizational or business goals are achieved. Direct costs

Vaccination costs
Side effect costs BENEFITS Identifying the intervention outcomes and classifying them as benefits or costs is the next step in conducting a CBA.
The results of interventions are broadly classified as:

health outcomes,
non-health outcomes, (reductions in time lost from work)
intangible outcomes,(reductions in health risks, pain, and suffering

decreased morbidity,
increased life expectancy,
averted medical costs as a result of early detection and treatment of the disease. Introduction Cost Benefit Analysis (CBA) is an economic evaluation technique that measures all the positive (beneficial) and negative (costly) consequences of a program in monetary terms. An 1844 paper by Jules Dupuit, "On the Measurement of the Utility of Public Works", is often cited as the first work on CBA. History what is CBA ??
CBA adopts a broad societal perspective (thus it includes all costs and all benefits), and
CBA measures the outcomes in monetary terms. CBA is the appropriate form of economic evaluation to assess the economic efficiency of public health-care interventions when health outcomes are disparate. Cost-benefit analysis helps you to

Decide whether to undertake a project or decide which of several projects to undertake.

Frame appropriate project objectives.

Develop appropriate before and after measures of project success.

Prepare estimates of the resources required to perform the project work. Its ALL about balance COSTS Everything gets a dollar value in a cost-benefit analysis. You can express some anticipated benefits in monetary equivalents (such as reduced operating costs or increased revenue). For other benefits, numerical measures can approximate, but NOT ALL If your project is to improve staff morale, for example, you may consider associated benefits to include reduced stress, increased productivity, Whenever possible, express benefits and costs in monetary terms to determine project’s net value. So what is benefit what is cost? Benefits are the monetary values of desirable consequences of economic policies . Benefits are generally classified as direct, indirect, and intangible: Indirect benefits are the prevented costs and savings resulting from the interventions but not related directly to them. Intangible benefits include the values of positive outcomes (e.g., reductions in health risk, pain, and suffering), which cannot be estimated from market data. Direct benefits are the values of desirable outcomes that can be estimated by using market-based data. Costs are the values of all the resources (e.g., labor, buildings, equipment, and supplies), tangible or intangible, used to produce a good or a service. Economists think of costs as consequences of choices. In the real world, resources are scarce. Because resources are limited, , the resources expended will not be available for other possible uses. For instance, the decision to allocate funds for a public health program renders these funds unavailable for education, housing, or defense spending. Therefore, the true cost of a program is not just the amount of funds spent on it. It is also the value of benefits that would have been derived if the resources had been allocated to their next best use. what questions need to be answered 3. Defining the Audience 4. Defining the Perspective 5. Defining the Time Frame and Analytic Horizon 6. Defining the Discount Rate Framing a CBA Framing a CBA involves these six steps: 1. Defining the Problem
2. Identifying Interventions
3. Defining the Audience
4. Defining the Perspective
5. Defining the Time Frame and Analytic Horizon
6. Defining the Discount Rate Decision Trees are excellent tools for helping you to choose between several courses of action. Decision Trees Choosing by Projecting "Expected Outcomes" Drawing a Decision Tree Evaluating Your Decision Tree CONS For example, when considering to go for a walk, you may look at the "Pros and Cons" of doing so, and decide whether walking is worth your time and effort or not. Some "Pros" might be that walking is a healthy activity that enhances your mental mindset and physical health. Some "Cons" might be that it requires work and you may get sweaty. HEALTY ACTIVITY
ENHANCE YOUR MENTAL MINDSET
ENHANCE PHYSICAL HEALTH YOU GET SWEATY
YOU CAN INJURY
WASTE OF TIME PROS – Mathematically well-stated: • Optimal solution,
• Complete ranking of the actions.

– Socio economically ill stated: • Single criterion? Not realistic. • Notion of criterion: perception thresholds, ... Multi-Criteria Decision Making MADM Multi-Attribute decision model:
Select (A1, A2,….,An,)
According to (a1, a2,…,an,) Example Construction Consider three cars x1, x2 and x3 to be evaluated with respect to two (p = 2) criteria C1 = fuel efficiency in $/km and C2 = size of engine in cm^3 with the following criteria impacts: MCDM’s consist of constructing a global preference relation for a set of alternatives evaluated using several criteria
Selection of the best actions from a set of alternatives, each of which is evaluated against multiple and often conflicting criteria
A broad set of methods aimed at representing the structure of the preferences of the decision maker facing the need to consider multiple objectives and criteria( e.g social, economic and environmental ones):
2 main families of methods: MADM and MODM What? Terminology Formalization of the decision problem with MCDM's MCDM definitions Multi-attribute decision methods(MADM): these methods approach problems that are assumed to have a predetermined, limited number of decision alternatives. MADM MCDM is concerned with structuring and solving decision and planning problems involving multiple criteria.
A single decision making is to choose among a countable or uncountable set of alternatives that s/he evaluates on the basis of two or more criteria
Multi-Criteria Decision Making (MCDM) is the study of methods and procedures by which concerns about multiple conflicting criteria can be formally incorporated into the management planning process MCDM Why? which aspects of the problem need to be explained. The aim of MCDM technique is to provide help and guidance to the decision making in discovering his or her most desired solution the problem.
The main purpose in most MCDM problems is to measure the overall preference values of the alternatives on some permissible scale. What is the nature of each intervention What is the technology used for the intervention What are the target population, the delivery site, and the personnel for delivering the intervention? What are the options? 1. Defining the Problem 2. Identifying Interventions Examples of Decision Problems Locating a new plant, new shop,
Choosing a new car,
Evaluating projects,
Selecting an investment strategy,
Selecting partner
---Religion
---Beauty
---Wealth
---Family status-relationship
---Education Problem solving with MCDM Conceptual Phase Establish the decision context, goal and identify the decision makers.
Identify the alternatives.
Identify the criteria that are relevant to the decision problem. Design Phase Assign scores to each alternative per each criterion.
Standardize the raw scores to generate decision table.
Determine a weight for each criterion to reflect how important it is to the overall decision. Choice Phase Use aggregation functions (or decision rules) to compute an overall score per alternative by combining the weights and standardized scores.
Perform a sensitivity analysis to assess the robustness of the preference ranking to changes in the criteria scores. Uni-criterion vs. Multi-criterion Decision Making Uni-criterion Model optimise: (f (a) a E A) Multi-criterion Model optimise: (f1(a), f2(a),..., fk (a)a E A) – Mathematically ill stated:
• No optimal solution, • No mathematicalmeaning.
– Socio economically well stated: • Closer to real world decision problem,
• Search for a compromise solution. Decision model:
- Max U = u( f1(a), … ,fk(a),…, fK(a) )
- with a unit of A
Where:
U is the total utility of the decision maker to be maximised ;
u is the function which expresses the utility for the K decisional criteria ;
fk(a) represents the status of the K criterion ;
A is an n-dimensional vector of decision variables. MODM Multi-objective decision methods(MODM): in this case the decision alternatives are not given, but defined by a set of problem constraints and identified using multiple objective programming. The number of potential decision alternatives may be large or infinite BAYES THEORY Introductıon SiMpLe StAtEmEnT
of
BaYeS tHeOrEm EXAMPLE 1. Structured Problems
 
These are familiar, straightforward, and clear
with respect to the information needed to
resolve them. They can be expected, and
managers can plan ahead and develop specific
ways to deal with them or even can take action
to prevent their occurrence. After preparing alternative solutions, the next
step in the decision-making process is to select
an alternative that seems to be most rational for
solving the problem. The alternative which is
selected must be communicated to those who
are likely to be affected by it. Acceptance of the
decision by group members is always desirable
and useful for its effective implementation. 5. Selecting the Best Solution Brainstorming is a popular tool that focuses on
throwing ideas onto the table without judging
them. Closely related to this is Reverse
Brainstorming.  This focuses upon how to cause
the problem rather than how to solve the
problem; the idea being that if you can cause
the problem, you can then figure out from there
how to solve the problem. Questions to Ask When Analyzing the Problem:

What is the history of the problem?  How long
has it existed?
How serious is the problem?
What are the causes of the problem?
What are the effects of the problem? In this stage of problem solving, questions
should be asked and information relevant to the
problem should be gathered so that critical
analysis of the problem is possible. This is how
the problem can be diagnosed. Managers should not make the mistake of assuming they know what is causing the problem without an effort to fully investigate the problem which is defined.
  2. Analyzing the Problem 3.Crisis Problems
 A crisis problem is an unexpected problem that
can lead to a disaster if not resolved quickly
and appropriately. Managers are installing
”early-warning” crisis information systems
and developing crisis management plans to
deal with them in the best possible ways. 2.Unstructured Problems

 Involve unclearness and information
deficiencies and often occur as new or
unexpected situations. They usually require novel solutions. Problem Solving vs.
Decision Making Feedback is the last step in the decision-making process. Here, the manager has to make built-in arrangements to ensure feedback for continuously testing actual developments against the expectations. It is like checking the effectiveness of follow-up measures.
Feedback is possible in the form of organised information, reports and personal observations. Feedback is necessary to decide whether the decision already taken should be continued or be modified in the light of changed conditions. 7. Ensuring Feedback After the selection of the best decision, the next
step is to convert the selected decision into an
effective action. Without such action, the
decision will remain merely a declaration of
good intentions. Here, the manager has to
convert 'his decision into 'their decision' through
his leadership. 6.Converting Decision into Action After the problem has been defined, diagnosed
on the basis of relevant information, the
manager has to determine available alternative
courses of action that could be used to solve the
problem at hand. Only realistic alternatives
should be considered. It is equally important to take
into account time and cost constraints and
psychological barriers that will restrict that number
of alternatives. 4. Developing Alternative Solutions After defining the problem and analyzing its
nature, the next step is to obtain the relevant
information/ data about it. There is information
flood in the business world due to new
developments in the field of information
technology. All available information should be
utilised fully for analysis of the solution. This
brings clarity to all aspects of the solution. 3. Collecting Relevant Data Identification of the real problem before a
business enterprise is the first step in the
process of decision-making. It is rightly said that
a problem well-defined is a problem half-solved.
Clear distinction should be made between the
problem and the symptoms which may cloud
the real issue. 1.Identifying the Problem Decision-making involves a number of steps
which need to be taken in a logical manner. This
is treated as a rational or scientific 'decision
making process' which is long and time
consuming. Such long process needs to be
followed in order to take rational/scientific
/result oriented decisions. Decision making process prescribes some rules and guidelines as to how a decision should be taken. This involves many steps logically arranged. The scientific method of decision making involves the following steps: Problem solving steps What is problem? Problem Solving vs. Decision Making Problem types EVALUATİON ATTRİBUTES The choise within the finite set of n alternative options (A1, A2,…, An) is made through their evaluation with respect to a finite number, K , of attributes or criteria (a1, a2, …, ak).
Each alternative presents a certain index of performance, defined by the score pkn. Selection of the best alternative within a define set:
-- SAW(Simple additive weighting)
--OWA(Ordered weighted averages)
--TOPSIS(Technique for order preference by similarity to the ideal solution
--ELECTRE(Elimination et choice translating reality)
--AHP(The analytical hierarchy process)
--SMART(The simple multi attiribute rating technique) LISTENING SCHOOL LIFE FRIENDS
Who will be using the results of the analysis?
What information does the audience need?
How will the results be used?
Patient perspective
Provider perspective
Payer perspective
Health-care system perspective
Government perspective
Societal perspective short enough that the outcomes are not unacceptably uncertain long enough:

to capture fully the costs and benefits that can readily be associated with the program, The discount rate is one parameter that can be varied in a sensitivity analysis to test its impact on the results of analysis and to make the results of studies based on different discount rates comparable. CDC recommends that a 3% social discount rate be used in analyses. CBA of a Strategy To Vaccinate Healthy Working Adults Against Influenza CBA of a Strategy To Vaccinate Healthy Working Adults Against Influenza This study was conducted in 2001 by K. Nichol to assess the economic implications of a strategy for annual vaccination of working adults in the United States aged 18–64 years.

Persons aged >64 years and other persons at high risk are more vulnerable to serious complications of influenza and are specifically targeted for annual vaccinations against influenza
The study problem was:
To compare the benefits of a program of nationwide vaccination of healthy working adults with its costs.

The questions that needed to be answered were:
What is the economic impact of influenza on the healthy adult
What would be the cost of implementing the vaccination program?
What would be the benefits of implementing the program? Vaccination

Subdermal injection of inactivated influenza virus vaccine

Healthy working adults aged 18–64 years

health department clinics, and public clinics in drug stores and grocery stores

Proposed vaccination strategy Who will use the results of the analysis?

Public health policy decisionmakers at local, state, and federal levels
Health research institutions and scientists

What information does the audience need?

What are potential benefits of a nationwide immunization strategy?
What are the direct and indirect costs of the program?

How will the results be used?

To determine the economic impact of a nationwide influenza vaccination strategy for working age adults. The CBA was conducted from a societal perspective The analytic horizon for the model was 1 year. The 1-year period was allowed to track the costs and benefits of a nationwide vaccination campaign and of side effects The study was conducted from a societal perspective; the discount rates used in the model were 5% and 3%.

The worst-case scenario used the 5% discount rate, while the base-case and best-case scenario results were estimated at the 3% discount rate. Productivity losses prevented

Work absenteeism costs prevented
Future lifetime earnings preserved as a result of deaths prevented
Reduced work effectiveness averted costs Direct costs averted

Health-care provider visit costs
Hospitalization costs Productivity losses

Productivity losses attributable to vaccination
Productivity losses attributable to potential side effects After all the benefits and costs have been estimated, the next and final step is the presentation of results in a simple and understandable form for the audience.
The two summary measures typically used are:

net present value (NPV), benefit-cost ratio (BCR). NPV is calculated by summing the dollar-valued benefits and then subtracting all of the dollar-valued costs, with discounting applied to both benefits and costs as appropriate. A CBA will yield a positive NPV if the benefits exceed the costs. Implementing such a program will generate a net benefit to society. The benefit-cost ratio (BCR) represents the ratio of total benefits over total costs, both discounted as appropriate For example, a BCR value of 1.2:1 will indicate that for every $1 invested (costs), society would gain $1.2 (benefits). Thomas Bayes First Mathematical Expression What We Know What We Want To Know MEDICINE ENGINEERING ECONOMICS MILITARY
STRATEGY PHILOSOPHY THEORY EVIDENCE Bayes' Theorem greatly improves the quality of decisions The probability P(A|B) of "A assuming B" is given by the formula P(A|B) = P(AB) / P(B) which for our purpose is better written as P(B|A)·P(A) = P(AB) = P(A|B)·P(B) QUESTION Because of high traffic,
if he decides to go
by car, there is a 50% chance he will be late. CAR TRAIN If he goes by bus,
which has special
reserved lanes but
is sometimes overcrowded,
the probability of being
late is only 20%. The commuter train is
almost never late, with a
probability of only 1%,
but is more expensive
than the bus. BUS P r{ bus } = P r{ car } = P r{ train } = 1/3

P r{ late | car } = 0.5

P r{ late | train } = 0.01

P r{ late | bus } = 0.2 0.5 × 1/3
=
0.5 × 1/3 + 0.2 × 1/3 + 0.01 × 1/3

= 0.7042 By Bayes Theorem, this is

P r{ late | car }P r{ car }
=
P r{ late | car }P r{ car } + P r{ late | bus }P r{ bus } + P r{ late | train }P r{ train } ANSWER What does AHP answer? WHAT IS AHP ? What does AHP answer? Why Hiearchy ? An important part of the process is to accomplish these three steps AHP is a multicriteria decision making
technique that can help express the general decision operation by decomposing a
complicated problem into a multilevel hierarchical structure of objective, criteria
and alternatives (Sharma et al., 2008). The question “Which one do we choose?” or “Which one is the best ?” by selecting the best alternative that matches all of the decision maker’s criteria. When people faced with a complex problem in order to understand the problem better they must break down
the problem into its smaller constituent parts and construct a hierarchical model to represent it. • STATE THE OBJECTIVE:
– Select the best gadget•
DEFINE THE CRITERIA:
– Cost , motor power , comfort
• PICK THE ALTERNATIVES:– Broadwater , C&H , Picobuy Standart Preference Table Pairwise Comparisons Why not make up your
own preference table ? Because the standard preference
table has been determined by experienced researchers in AHP to
be a reasonable basis for
comparing two alternatives. Using pairwise comparisons, the relative importance of one criterion over another can be expressed.


Cost is 2 times as important as reliability

Comfort is 4 times as important as style Comparison of criterias Vocational training Collage Prep Music classes Listening Friends School life Multiply each column of the pairwise comparison matrix by its priority.

Divide these number by their priorities.

Then, average the results to get lmax. Consistency CI = λmax – n CR: consistency ratio
n – 1 CR: CI / RI

CI: consistency index
RI: random consistency index (you can see from table)

Since the consistency ratio, CR, is less than .10,
this is well within the acceptable range for
consistency. Criterias: C1, C2,...,CpAlternatives: x1, x2,..., xp. where xk (for k=1, 2,...,p) is a raw measure of the impact of x in the criterion Ck

The criterion specific score of the alternative xp with respect to the criterion Ck

The general MCDM problem is to evaluate F(xp)=(f1(xp), ... , fk(xp)) , p=1, 2, ...m and determine the overall values of the alternatives or simply select the best alternative x* Decision Making Steps There are different views on decision making steps but most of them cover 7 steps that should be done properly. These steps are;
1) Identifying the problem or opportunity
2) Gathering information
3) Developing alternatives
4) Evaluating alternatives
5) Making the decision
6) Taking action and implementing the decision
7) Learning from and reflecting on the decision Identifying the Problem or Opportunity In this step, decision makers think of the problem or opportunity and try to estimate if solving the problem or taking action about the opportunity will worth it. Gathering Information 1) Decision makers gather information
about the subject
2) Determine if the information is relevant or not about the subject
3) Analyse similar cases that had happened before
4) Determine who can help or has the power to make the decision happen Developing alternatives In this step, decision makers analyse the gathered information, brainstorm about what can be done about the situation and generate possible solutions. Creativity and thinking divergently is important in this step. Evaluating alternatives In this step, every option is considered in terms of feasibilty, reasonbility and acceptability. Pros and cons of every possible solution is listed andthe best option is chosen. Contrary to the 4th step thinking convergently is important in this step. Taking Action In this step, the best option which was chosen in
step 5 is made as a decision and a plan is put to implement it. Reflecting on the Decision After the decision is made, some problems may
occur. Reflecting on these problems is essential
to make the actual decision a good one. Making the Decision After all the alternatives are evaluated, the best option which
seems the best and covering all the criterias is made as a decision. Decision Making Stages According to psychologist B. Aubrey Fisher there are 4 stages in
group decision making. These stages are;
1) Orientation stage
2) Conflict stage
3) Emergence stage
4) Reinforcement stage Orientation Stage: In this stage group members start knowing
each other and try to communicate effectively.
Conflict Stage: After group members start to know each other little arguments and disputes occur between group members.
Emergence Stage: The group members start to clear up on some opinions by further talking about them.
Reinforcement Stage: A final decision is made and members try to justify themselves that it was the right decision. The Elements of DECISION TREES SELECTİON OF THE MCDM DECİSİON RULE The following criteria for the selection of the method to be adopted1.Internal consistency and logical soundness;2.Transparency;3.Ease of use;4.Data requirements are consistent with the importance of the issue being considered;5.Realistic time and manpower resource requirements for the analytical process6.Ability to provide an audit trail;7.Software availability, where needed. Drawing a Decision Tree Evaluating Your Decision Tree -Are simple to understand and interpret.
-Possible scenarios can be added
-Worst, best and expected values can be determined for different scenarios
-Can be combined with other decision techniques. -Calculations can get very complex particularly if many values are uncertain
-Hard to determine when many outcomes are linked ADVANTAGES DISADVANTAGES Applying truth values
Full transcript