Logical Decisions - Classweb

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no intrinsically correct shape for a SUF, the assessment process must be subjective. There are two commonly used methods for assessing a SUF -- mid-level splitting and assessments using probabilities. These approaches have different theoretical foundations that are mostly of academic interest. If you know the differences, you will know which technique you will want to use. If not, use the technique you feel most comfortable with. SUF Assessment using Mid-Level Splitting. The mid-level splitting procedure seeks to identify the level that is exactly midway (half-way) in preference between a low level and a high level for a measure. The SUF::Assess Value option implements the mid-level splitting procedure in LDW. Remember from the discussion on page 9-15 that this mid-preference level could well be different from the average of the two ends of the range. You define the mid-preference level by asking the decision maker questions about changes in the measure. Specifically the midpreference level (call it L) is where you prefer a change from the least preferred level (call it L0) to L and a change from L to the most preferred level (call it L1) equally. In other words, you want to find the level L that divides the range from L0 to L1 into two pieces, each representing an equal change in utility. In more mathematical terms, if U(x) represents the SUF for the measure, we want to find the point where U(L) - U(L0) = U(L1) - U(L). Remember that you should always prefer L to L0 and you should always prefer L1 to L. However, you still may feel that the change from L0 to L is more significant or important than the change from L to L1. You may feel this even though the result of the second change (L1) is the most preferred level overall. Assume when asking these questions about one measure that the levels of all of the other measures remain constant. You should think of the questions of in terms of simplified hypothetical alternatives, even if the levels in the questions are similar to those for the real alternatives. If the decision maker cannot answer the questions without knowing a specific level of another measure, there may be a preferential dependence between the two measures. Modeling preference dependencies is beyond the current abilities of LDW. 9-16 Section 9 -- In Depth
For an example of the mid-level splitting approach, consider the truck example used in the Tutorial. Suppose that the range of available horsepowers in the different trucks being considered is 80 to 160. To establish the mid-preference point you might ask the following series of questions (illustrated in Figure 9-3): Figure 9-3. Example of SUF assessment process Q1: The range on power is from 80 hp to 160 hp. Suppose you are thinking of buying a truck with the best levels on all of the other measures, including price, but with only 80 hp. Call this truck A. Now suppose I tell you that I have found another truck that has 120 hp but still has the same levels on the other measures, including cost. Call Section 9 -- In Depth 9-17
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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
Page 211 and 212: Figure 8-38. Example of Results::Gr
Page 213 and 214: Finally, the two radio buttons on t
Page 215 and 216: 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: Figure 9-2. Example of linear (stra
Page 265 and 266: Since U(L0) = U(80) = 0 and U(L1) =
Page 267 and 268: Figure 9-5. Summary of SUF assessme
Page 269 and 270: describe two alternatives: A, which
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
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Page 309 and 310: A probability of less than 0.5 for
Page 311 and 312: Interpreting the Ranking Results LD
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S E C T I O N Examples 10
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the idea that other manufactures an
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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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