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Journal of Mechanical Design | Volume 129 | Issue 10 | Research Paper
RESEARCH PAPERS

A Method to Ensure Preference Consistency in Multi-Attribute Selection Decisions

[+] Author and Article Information
Michael Kulok

Department of Mechanical and Aerospace Engineering, University at Buffalo-SUNY, Buffalo, NY 14260

Kemper Lewis1

Department of Mechanical and Aerospace Engineering, University at Buffalo-SUNY, Buffalo, NY 14260kelewis@buffalo.edu

1

Corresponding author.

J. Mech. Des 129(10), 1002-1011 (Dec 18, 2006) (10 pages) doi:10.1115/1.2761921 History: Received July 20, 2006; Revised December 18, 2006
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A number of approaches for multi-attribute selection decisions exist, each with certain advantages and disadvantages. One method that has recently been developed, called the hypothetical equivalents and inequivalents method (HEIM) supports a decision maker (DM) by implicitly determining the importances a DM places on attributes using a series of simple preference statements. In this and other multi-attribute selection methods, establishing consistent preferences is critical in order for a DM to be confident in his/her decision and its validity. In this paper, a general preference consistency method is developed, which is used to ensure that a consistent preference structure exists for a given DM. The method is demonstrated as part of HEIM, but is generalizable to any cardinal or ordinal preference structure, where the preferences can be over alternatives or attributes. These structures play an important role in making selection decisions in engineering design including selecting design concepts, materials, manufacturing processes, and configurations, among others. The theoretical foundations of the method are developed and the need for consistent preferences is illustrated in the application to a drill selection case study where the decision maker expresses inconsistent preferences.
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References

1
Saaty, T. L., 1980, "The Analytic Hierarchy Process", McGraw-Hill, New York.
2
Keeney, R. L., and Raiffa, H., 1993, "Decision With Multiple Objectives: Preferences and Value Tradeoffs", Cambridge University Press, Cambridge, UK.
3
Thurston, D. L., 1991, “A Formal Method for Subjective Design Evaluation With Multiple Attributes,” Res. Eng. Des.  [CrossRef], 3 , pp. 105–122.
4
Wan, J., and Krishnamurty, S., 2001, “Learning-Based Preference Modeling in Engineering Design Decision-Making,” ASME J. Mech. Des.  [CrossRef], 123 (2), pp. 191–198.
5
Wassenaar, H. J., and Chen, W., 2003, “An Approach to Decision Based Design With Discrete Choice Analysis for Demand Modeling,” ASME J. Mech. Des.  [CrossRef], 125 (3), pp. 490–497.
6
Green, P. E., and Srinivasan, V., 1990, “Conjoint Analysis in Marketing: New Developments With Implications for Research and Practice,” J. Marketing, 54 (4), pp. 3–19.
7
Scott, M. J., and Antonsson, E. K., 2005, “Compensation and Weights for Trade-Offs in Engineering Design: Beyond the Weighted Sum,” ASME J. Mech. Des.  [CrossRef], 127 (6), pp. 1045–1055.
8
Scott, M. J., and Antonsson, E. K., 1998, “Aggregation Function for Engineering Design Trade-Offs,” Fuzzy Sets Syst.  [CrossRef], 99 (2), pp. 253–264.
9
Otto, K. N., and Antonsson, E. K., 1991, “Trade-Off Strategies in Engineering Design,” Res. Eng. Des.  [CrossRef], 3 (2), pp. 87–104.
10
Eschenauer, H., Koski, J., and Osyczka, A. E., 1990, "Multicriteria Design Optimization: Procedures and Applications", Springer-Verlag, New York.
11
Saari, D. G., 2000, “Mathematical Structure of Voting Paradoxes. I; Pairwise Vote. II; Positional Voting,” Economic Theory, 15 (1), pp. 1–103.
12
Stewart, T. J., 1992, “A Critical Survey on the Status of Multiple Criteria Decision Making Theory and Practice,” Omega, 20 (5–6), pp. 569–586.
13
Fukuda, S., and Matsuura, Y., 1993, “Prioritizing the Customer’s Requirements by AHP for Concurrent Design,” "ASME", Design for Manufacturability, DE-52, pp. 13–19.
14
Benyon, M., Curry, B., and Morgan, P., 2000, “The Dempster–Shafer Theory of Evidence: An Alternative Approach to Multicriteria Decision Modeling,” Omega, 28 (1), pp. 37–50.
15
Davis, L., and Williams, G., 1994, “Evaluating and Selecting Simulation Software Using the Analytic Hierarchy Process,” Integr. Manuf. Syst., 5 (1), pp. 23–32.
16
Basak, I., and Saaty, T. L., 1993, “Group Decision Making Using the Analytic Hierarchy Process,” Math. Comput. Modell.  [CrossRef], 17 (4–5), pp. 101–110.
17
Hamalainen, R. P., and Ganesh, L. S., 1994, “Group Preference Aggregration Methods Employed in AHP: An Evaluation and an Intrinsic Process for Deriving Members’ Weightages,” Eur. J. Oper. Res., 79 (2), pp. 249–265.
18
Scott, M., 2002, “Quantifying Certainty in Design Decisions: Examining AHP,” "ASME Design Technical Conferences, Design Theory and Methodology Conference", DETC2002/DTM, Paper No. 34020.
19
Barzilai, J., and Golany, B., 1990, “Deriving Weights From Pairwise Comparison Matrices: The Additive Case,” Oper. Res. Lett., 96 , pp. 407–410.
20
Barzilai, J., Cook, W. D., and Golany, B., 1992, “The Analytic Hierarchy Process: Structure of the Problem and Its Solutions,” "Systems and Management Science by Extremal Methods", F.Y.Phillips and J.J.Rousseau, eds. Kluwer Academic Publishers, Netherlands, pp. 361–371.
21
Dym, C. L., Wood, W. H., and Scott, M. J., 2002, “Rank Ordering Engineering Designs: Pairwise Comparison Charts and Borda Counts,” Res. Eng. Des., 13 , pp. 236–242.
22
US News and World Report, 2005, “America’s Best Colleges,” http://www.usnews.com/usnews/rankguide/rghome.htm
23
Peter, H., and Wakker, P., 1991, “Independence of Irrelevant Alternatives and Revealed Group Preferences,” Econometrica, 59 (6), pp. 1787–1801.
24
See, T. K., Gurnani, A., and Lewis, K., 2005, “Multi-attribute Decision Making Using Hypothetical Equivalents and Inequivalents,” ASME J. Mech. Des.  [CrossRef], 126 (6), pp. 950–958.
25
Scott, M. J., and Zivkovic, I., 2003, “On Rank Reversals in the Borda Count,” "ASME Design Technical Conferences", Design Theory and Methodology Conference, DETC2003/DTM, Paper No. 48674.
26
Chen, W., Wiecek, M., and Zhang, J., 1999, “Quality Utility: A Compromise Programming Approach to Robust Design,” ASME J. Mech. Des., 121 (2), pp. 179–187.
27
Dennis, J. E., and Das, I., 1997, “A Closer Look at Drawbacks of Minimizing Weighted Sums of Objective for Pareto Set Generation in Multicriteria Optimization Problems,” Struct. Optim.  [CrossRef], 14 (1), pp. 63–69.
28
Messac, A., Sundararaj, J. G., Tappeta, R. V., and Renaud, J. E., 2000, “Ability of Objective Functions to Generate Points on Non-Convex Pareto Frontiers,” AIAA J., 38 (6), pp. 1084–1091.
29
Zhang, J., Chen, W., and Wiecek, M., 2000, “Local Approximation of the Efficient Frontier in Robust Design,” ASME J. Mech. Des.  [CrossRef], 122 (2), pp. 232–236.
30
Scott, M. J., and Antonsson, E. K., 2000, “Using Indifferent Points in Engineering Decisions,” "ASME Design Engineering Technical Conferences", Design Theory and Methodology Conference, DETC2000/DTM, Baltimore, MD, Paper No. 14559.
31
Wu, G., 1996, “Exercises on Tradeoffs and Conflicting Objectives,” Harvard Business School Case Studies, 9-396-307.
32
Gurnani, A., See, T. K., and Lewis, K., 2003, “An Approach to Robust Multiattribute Concept, Selection,” "ASME Design Technical Conferences", Design Automation Conference, DETC03/DAC, Paper No. 48707.
33
Gurnani, A., and Lewis, K., 2005, “Robust Multiattribute Decision Making Under Risk and Uncertainty in Engineering Design,” Eng. Optimiz.  [CrossRef], 37 (8), pp. 813–830.
34
See, T. K., and Lewis, K., 2006, “A Formal Approach to Handling Conflicts in Multiattribute Group Decision Making,” ASME J. Mech. Des.  [CrossRef], 128 (4), pp. 678–688.
35
Thurston, D. L., 2001, “Real and Misconceived Limitations to Decision Based Design With Utility Analysis,” ASME J. Mech. Des.  [CrossRef], 123 (2), pp. 176–182.
36
Hey, J., and Orme, C., 1994, “Investigating Generalizations of Expected Utility Theory Using Experimental Data,” Econometrica, 62 (6), pp. 1291–1326.
37
Hey, J., and Carbone, E., 1995, “A Comparison of the Estimates of EU and Non-EU Preference Functionals Using Data from Pairwise Choice and Complete Ranking Experiments,” Geneva Papers on Risk and Insurance Theory, 20 (2), pp. 111–133.
38
Hey, J. D., 1998, “Do Rational People Make Mistakes?” in "Game Theory, Experience, Rationality", W.Leinfellner, and E.Kohler, eds., Kluwer Academic Publishers, Netherlands, pp. 55–66.
39
Hammond, K., 1996, "Human Judgment and Social Policy", Oxford University Press, New York.
40
Yu, P. L., 1985, "Multiple-Criteria Decision Making: Concepts, Techniques and Extensions", Plenum Press, New York, pp. 113–161.
41
Andreoni, J., and Miller, J., 2002, “Giving According to GARP: An Experimental Test of the Consistency of Preferences for Altruism,” Econometrica, 70 (2), pp. 737–753.
42
Chiclana, F., Herrera, F., and Herrera-Viedma, E., 2001, “Integrating Multiplicative Preference Relations in a Multipurpose Decision-Making Model Based on Fuzzy Preference Relations,” Fuzzy Sets Syst., 122 , pp. 277–291.
43
Pindyck, R. S., and Rubinfeld, D. L., 2001, "Microeconomics", 5th ed., Prentice Hall, Englewood Cliffs, NJ.
44
Wakker, P. P., 1988, "Additive Representations of Preferences: A New Foundation of Decision Analysis", Kluwer Academic Publishers, Netherlands.
45
Kulok, M., 2004, “A Study of Consistency in Multi-attribute Decision Making,” MS thesis, State University of New York at Buffalo, Buffalo, NY.
46
Maddulapalli, K., Azarm, S., and Boyars, A., 2005, “Interactive Product Design Selection With an Implicit Value Function,” ASME J. Mech. Des.  [CrossRef], 127 (3), pp. 367–377.
47
Phadke, M. S., 1989, "Quality Engineering Using Robust Design", Prentice Hall, Englewood Cliffs, NJ.
48
Arrow, K. J., and Raynaud, H., 1986, "Social Choice and Multicriterion Decision-Making", Massachusetts Institute of Technology, Boston, MA.

Figures

Grahic Jump Location
+Value function representations
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Value function representations
Figure 1

Value function representations

Grahic Jump Location
+Feasible design space
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Feasible design space
Figure 2

Feasible design space

Grahic Jump Location
+Feasible design space reduction
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Feasible design space reduction
Figure 3

Feasible design space reduction

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