Logical Decisions - Classweb

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Figure 9-5 summarizes the process of SUF assessment using the mid-level splitting method. In box 1, the decision maker is asked which change is more preferred, one from 80 to 110 hp or one from 110 to 180 hp. In box 2, the decision maker answers that the changes are equally preferred. This implies that 110 is the mid-preference level for the range from 80 to 180 hp. In box 3, we assign utilities to the three levels. the least preferred level of 80 hp is assigned U = 0 by definition. The most preferred level 180 is assigned U = 1, also by definition. The mid-preference level of 110 is assigned the average of the two other utilities or U = 0.5. In box 4, a graph of utility vs. horsepower is shown with a smooth curve fit between the three known points. This curve defines a SUF for horsepower for the range 80 to 160 hp. Note that technically a preference function assessed using the mid-level splitting technique should be called a measurable value function rather than a utility function. Disadvantages of the Mid-level Splitting Method. The midlevel splitting method is difficult to use if your measure scale is not continuous. For example, if a measure consists of, say, five specially defined scale points, it may not be the case that one point is the mid-preference level between two others. In addition, the requirement of using changes in levels rather than the levels directly is difficult for some decision makers. If either of these problems arises it may be easier to use the probability method described below. SUF Assessment Using Probabilities. The second approach for assessing SUFs involves asking questions that involve uncertain levels of the measure for some hypothetical alternatives. The probability assessment method is implemented in LDW as the SUF::Assess Utility option. The general idea is to find an alternative with a certain (point estimate) level on a measure that is equally preferred to an alternative with well-defined probabilities of having two different levels, each of whose utilities is known. As an example, we will use the resale value of the truck after three years (as a percentage of its purchase price). We could 9-22 Section 9 -- In Depth
describe two alternatives: A, which is a truck with a single known resale value and B, which is a truck with a well-defined probability of getting one of two resale values. The dialogue for assessing the mid-preference level for resale value using the probability approach might go as follows (illustrated in Figure 9-6): Figure 9-6. Example of SUF assessment using probability approach Q1: The resale value range is from 40 to 70 percent of purchase price. Suppose you were thinking of buying a truck with the best levels on all of the Section 9 -- In Depth 9-23
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Logical Decisions Decision Support
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Table of Contents Table of Contents
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Assessing Weights with Weight Ratio
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Assessing Interactions Between Meas
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Introduction Real decisions aren't
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S E C T I O N Requirements and Inst
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"Logical Decisions". This program g
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Quick Start Introduction This secti
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Defining goals and measures. In LDW
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Figure 3-1. The SUF for "Years of E
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weights of the measures. All of the
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S E C T I O N Basic Tutorial 4
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Figure 4-1. Tutorial overview. 4-2
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Now lets make sure the alternatives
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Assume you have decided that you wi
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Next we will enter the measures for
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Defining Preferences The alternativ
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1. Select the Assess::Common Units
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almost equally unacceptable, while
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1. Select the Assess::Common Units
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When you do this, the tradeoff grap
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1. Select "Performance" and "Price"
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8. Click on the "Equal" button to t
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Figure 4-11. Display generated by R
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Figure 4-13. Overall ranking for tr
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Figure 4-15. Graph showing sensitiv
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You can see the completed introduct
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Advanced Tutorial This tutorial sec
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Probabilities There is a problem wi
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This information indicates that the
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A uniform distribution is defined b
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On the left is a list of the possib
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Figure 5-2. Example of Results::Unc
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screen a large database for the alt
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9. LDW will ask if you want to appe
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commit to buying their truck before
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see that the rankings for all the a
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S E C T I O N Using LDW 1: Structur
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The Edit::Insert option. The Insert
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! Summary -- view a dialog box that
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structure like an organization char
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If you check the Show Assessment St
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saves it for later pasting. When yo
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You can create a new Matrix view by
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The quick entry view shows the alte
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Structuring Goals The goals in an L
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these two fields to describe each m
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the hierarchy. In the Matrix view,
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! Point Estimate -- use a single nu
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Figure 6-12. Example of a measure l
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Figure 6-14. Example of a measure l
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pass, LDW replaces each probabilist
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Figure 6-17. Dialog box for definin
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Figure 6-18. Measure Category Dialo
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S E C T I O N Using LDW 2: Assessin
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measure utility functions for the g
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information as possible when you ch
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measures with categories require mu
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The "Reset" button deletes any asse
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You can change the shape of the cur
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Figure 7-4. Utility Assessment Scre
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very different from the average of
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Figure 7-6. Assessment matrix for A
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You can, however, leave the assessm
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properties dialog box can be select
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the same level. LDW provides a grap
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options in the Hierarchy menu to ad
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The check box labeled "Allow Repres
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Next you will see a tradeoff assess
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The Tradeoff::Use Alternatives to S
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Figure 7-13. Example of Direct Entr
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You can think of the importance num
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Figure 7-15. Assessment Screen for
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When you have selected two members
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("importance strength") that best d
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clicking on the "Initialize" button
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Set a Small k. The Enter Small k op
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select the tradeoff you would like
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Figure 7-18. Effects of consistency
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Using LDW 3: Reviewing Results Intr
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The curve shows how the utility fun
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The tradeoff graph has one measure
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When you select the option, you are
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the relative weights of the "Price"
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epresents a computer alternative wi
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Figure 8-11. Example of Review::Ass
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e true even if the measure has a ve
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an analysis are included in exactly
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Graph Weights The Graph Weights dis
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Figure 8-16. Results::Rank Alternat
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Figure 8-18. Dialog box for Results
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You can use the measure equivalents
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simulation for each alternative usi
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Sensitivity Graphs Sensitivity grap
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You can view a sensitivity table by
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Figure 8-28. Example of Results::Sc
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Figure 8-30. Example of Results::Sc
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In the dialog box, you are asked to
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Figure 8-34. Dialog box for Results
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Graph an Alternative The graph an a
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Figure 8-38. Example of Results::Gr
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Finally, the two radio buttons on t
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Figure 8-43. Example of Results::Co
Page 217 and 218: Printing and Saving Windows You can
Page 219 and 220: The dialog box will show you the fi
Page 221 and 222: Figure 8-45. Dialog box for Edit::C
Page 223 and 224: Changing the range for utility. You
Page 225 and 226: Figure 8-50. Dialog box for Prefere
Page 227 and 228: the current color for that type of
Page 229 and 230: copies the selected objects to the
Page 231 and 232: analysis with the skeleton analysis
Page 233 and 234: Figure 8-55. Dialog box for File::I
Page 235 and 236: the other measures. The measure nam
Page 237 and 238: The idea of the Import Structure op
Page 239 and 240: Next, LDW asks you if it should app
Page 241 and 242: Other Options utility function for
Page 243: In addition, the Window menu contai
Page 247 and 248: In Depth Introduction This section
Page 249 and 250: A third example is a portfolio deci
Page 251 and 252: Each alternative has a raw score (c
Page 253 and 254: into more specific goals continues
Page 255 and 256: Measures in LDW You define measures
Page 257 and 258: computed measure levels to common u
Page 259 and 260: Converting the Measures to Common U
Page 261 and 262: Figure 9-2. Example of linear (stra
Page 263 and 264: For an example of the mid-level spl
Page 265 and 266: Since U(L0) = U(80) = 0 and U(L1) =
Page 267: Figure 9-5. Summary of SUF assessme
Page 271 and 272: with equal chances of 40 and 70 per
Page 273 and 274: In the original formulation of the
Page 275 and 276: 1 Equal Importance Two activities c
Page 277 and 278: You begin the process by selecting
Page 279 and 280: Figure 9-7. Effects of goals with a
Page 281 and 282: 0.5. Then the weight assigned to "P
Page 283 and 284: ! You can use the "Smarter Method"
Page 285 and 286: allocates this weight before comput
Page 287 and 288: nth root of the product of the rati
Page 289 and 290: Figure 9-8. Summary of estimating t
Page 291 and 292: on the decision maker's response, L
Page 293 and 294: Figure 9-10. MUF assessment figure
Page 295 and 296: Now think of adjusting P so that th
Page 297 and 298: Another approach is to use the rang
Page 299 and 300: Figure 9-12. Quantitative range vs.
Page 301 and 302: If a measure’s range changes, LDW
Page 303 and 304: Figure 9-14 is an example of the ov
Page 305 and 306: Similarly, a single member can have
Page 307 and 308: chance having 160 hp (the most pref
Page 309 and 310: A probability of less than 0.5 for
Page 311 and 312: Interpreting the Ranking Results LD
Page 313: S E C T I O N Examples 10
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The completed goals hierarchy is sh
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Buying a House The ranking results
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Figure 10-5. Goals hierarchy for bu
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Overall goal Quality goal Costs goa
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The preference assessments were don
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Figure 10-9. Goals hierarchy for re
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! Noise, ! Agricultural Impacts, an
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S E C T I O N Commands Summary 11
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Assess Menu Edit Menu The Assess me
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File Menu Edit::Insert Lets you add
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utility function” if the active g
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Matrix Menu ! Hierarchy -- options
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Results::Dynamic Sensitivity See th
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Review::Compute Utilities Compute t
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Tradeoff Menu View Menu LDW display
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S E C T I O N Glossary 12
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Common Units Certainty Equivalent C
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LDW File Level Lottery Measure assi
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MUF MUF Formula See also: Alternati
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Preference Set Probabilistic Level
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Tradeoff Trial program decides whic
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Bibliography B
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The classic reference on multiple m
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Appendix This appendix describes th
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= .125 Thus the weight for cost is
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Index adjusted AHP ................
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computing ................8 - 3 int
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