Logical Decisions - Classweb

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Identifying and Defining Alternatives in LDW Initially, an LDW alternative is just a name, limited to 255 characters, and optionally an ID number or a comment. The real definition of an alternative is its levels on the evaluation measures. You define the levels in LDW's Matrix View. LDW options let you define measure levels with probabilities or with measure categories. If you have many alternatives you my find it easiest to define them outside LDW and to use the File::Import option to load them into LDW. You can read more about how to define alternatives on page 6-14. You can read about defining levels with probabilities on page 6-21 and about defining levels with measure categories on page 6-30. The File::Import option is discussed on page 8-64. Identifying Goals and Objectives Goals and objectives are the qualitative considerations that influence the desirability of the alternatives. For example, in choosing a car the highest level goal might be "choose the best car." Underneath this broad goal might be dozens of subsidiary concerns, such as "minimize the price of the car," "maximize power," "maximize fuel economy," and "maximize rear seat legroom." Some of these concerns may overlap, some may be conflicting and some may be unimportant when compared to the other concerns. LDW uses a Goals Hierarchy to help you organize the goals and objectives for an analysis. Developing a Goals Hierarchy A goals hierarchy is like an organization chart. It starts with the most general goals at the top and breaks these general goals down into more specific sub-goals. In the truck example from the Tutorial, the general goal of "choose the best truck" might be expanded into "minimize cost," "maximize quality," and "maximize features." You might break the "maximize features" objective down further into "maximize performance" and "maximize comfort." Figure 9-1 shows how the top portion of a goals hierarchy for buying a truck might look. The process of dividing general goals 9-6 Section 9 -- In Depth
into more specific goals continues until the objectives are specific enough to measure. In our example, "minimize cost" might be specific enough to measure although it is near the top of the hierarchy, while we would probably have to break "maximize performance" down further before we could develop meaningful measures. Measures are discussed further on page 9-8. Figure 9-1. Example goals hierarchy. Goals and Objectives in LDW LDW uses goals to organize the measures into a hierarchy. LDW's goals correspond to those in a goals hierarchy. The lowest level goals serve to aggregate related evaluation measures, while higher level goals can aggregate both measures and other goals. There is always a highest level goal (initially called "Overall") corresponding to the highest level in the goals hierarchy. Lower level goals can be added and revised using the View::Goals Hierarchy option. The measures and other goals that belong to a goal are called its members. LDW requires that the lowest level Section 9 -- In Depth 9-7
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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
Page 201 and 202: Figure 8-28. Example of Results::Sc
Page 203 and 204: Figure 8-30. Example of Results::Sc
Page 205 and 206: In the dialog box, you are asked to
Page 207 and 208: Figure 8-34. Dialog box for Results
Page 209 and 210: 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
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Page 239 and 240: Next, LDW asks you if it should app
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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: Each alternative has a raw score (c
Page 255 and 256: Measures in LDW You define measures
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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 and 268: Figure 9-5. Summary of SUF assessme
Page 269 and 270: describe two alternatives: A, which
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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"
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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
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Figure 9-14 is an example of the ov
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Similarly, a single member can have
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chance having 160 hp (the most pref
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A probability of less than 0.5 for
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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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