Multiple objectives decision making (MODM) in engineering design refers to obtaining a preferred optimal solution in the context of conflicting design objectives. Problems with multiple objectives do not have a unique optimal solution but a set of Pareto optimal solutions. This paper presents a new interactive multistage MODM method which captures a decision maker’s preference structure in order to obtain a preferred Pareto solution even for non-convex problems. Representative subsets of an entire Pareto optimal set are generated and expanded based on the decision maker’s preference. The ε-constraint method is used to constrain the multiple objectives problem based on the decision maker’s feedback. In addition, ideas from an interactive weighted Tchebycheff approach are applied to reduce the feasible region at each stage, ensuring that the process eventually converges to a preferred solution. The method is demonstrated with two examples: (i) a simple two-bar truss design, and (ii) a more complicated problem in power electronic module design.

1.
Arora, J. S., Introduction to Optimum Design, McGraw-Hill, New York, 1989.
2.
Chankong, V., and Haimes, Y. Y., 1978, “The Interactive Surrogate Worth Tradeoff Method for Multiple Objectives Decision Making,” Multiple Criteria Problem Solving, Edited by Zionts S., Lecture Notes in Economics and Mathematical Systems 155, Springer-Verlag, Berlin, pp. 42–67.
3.
Chankong, V., and Haimes, Y. Y., 1983, Multiobjective Decision Making: Theory and Methodology, Elsevier Science Publishing Co., Inc., New York.
4.
Charnes, A., and Cooper, W. W., 1961, Management Models and Industrial Applications of Linear Programming, Vol. 1, John Wiley & Sons, Inc., New York.
5.
Das
I.
, and
Dennis
J. E.
,
1997
, “
A Closer Look at Drawbacks of Minimizing Weighted Sums of Objectives for a Pareto Set Generation in Multicriteria Optimization Problems
,”
Structural Optimization
, Vol.
14
, pp.
63
69
.
6.
Diaz
A.
,
1987
, “
Interactive Solution to Multiobjective Optimization Problems
,”
International Journal for Numerical Methods in Engineering
, Vol.
24
, pp.
1865
1877
.
7.
Eschenauer, H., Koski, J., and Osyczka, A., (Editors), 1990, Multicriteria Design Optimization, Springer-Verlag, New York.
8.
Frank, M., and Wolfe, P., 1956, “An Algorithm for Quadratic Programming,” Naval Research Logistics Quarterly 3, No. 1–2, pp. 95–110.
9.
French, S., 1988, Decision Theory: An Introduction to the Mathematics of Rationality, Ellis Horwood Limited, London.
10.
Gass
S.
, and
Saaty
T.
,
1955
, “
The Computational Algorithm for the Parametric Objective Function
,”
Naval Research Logistics Quarterly
,
2
, pp.
39
45
.
11.
Geoffrion
A. M.
,
Dyer
J. S.
, and
Feinberg
A.
,
1972
, “
An Interactive Approach For Multiple Criteria Optimization with an Application to the Operation of an Academic Department
,”
Management Science
,
19
, No.
4
, pp.
357
368
.
12.
Haimes, Y. Y., Wismer, D. A., and Lasdon, L. S., 1971, “On a Bicriterion Formulation of the Problems of Integrated System Identification and System Optimization,” IEEE SMC-1, pp. 296–97.
13.
Hwang, C. L., and Masud, A. S. M., 1979, Multiple Objective Decision Making-Methods and Applications: A State of the Art Survey, Springer-Verlag, Berlin.
14.
Kirsch, U., 1981, Optimal Structural Design, McGraw-Hill, New York.
15.
Kumar
N.
, and
Tauchert
T. R.
,
1992
, “
Multiobjective Design of Symmetrically Laminated Plates
,”
ASME JOURNAL OF MECHANICAL DESIGN
, Vol.
114
, pp.
620
625
.
16.
Lasdon, L. S., Waren, A. D., Jain, A., and Ratner M., 1970, “Design and Testing of a GRG Code for Nonlinear Programming,” ACM Trans. Math. Software, 4, pp. 34–50.
17.
Matsumoto
M.
,
Abe
J.
, and
Yoshimura
M.
,
1993
, “
A Multiobjective Optimization Strategy with Priority Ranking of Design Objectives
,”
ASME JOURNAL OF MECHANICAL DESIGN
, Vol.
115
, pp.
784
792
.
18.
Michelena
N. F.
, and
Agogino
A. M.
,
1988
, “
Multiobjective Hydraulic Cylinder Design
,”
ASME JOURNAL OF MECHANICAL DESIGN
, Vol.
110
, pp.
81
87
.
19.
Miettinen, K., 1997, “Review of Nonlinear MCDM Methods,” 6th International Summer School of MCDA, Turku, Finland.
20.
Miller
G. A.
,
1956
, “
The Magical Number Seven Plus or Minus Two: Some Limits on our Capacity for Processing Information
,”
Psychological Review
, Vol.
63
, pp.
81
97
.
21.
Papalambros, P. Y., and Wilde, D. J., 1988, Principles of Optimal Design, Cambridge University Press, Cambridge.
22.
Pecht, M., 1994, Integrated Circuit, Hybrid and Multichip Module Package Design Guidelines, A Focus On Reliability, John Wiley & Sons, Inc., New York.
23.
Rao
S. S.
, and
Eslampour
H. R.
,
1986
, “
Multistage Multiobjective Optimization of Gearboxes
,”
ASME JOURNAL OF MECHANICAL DESIGN
, Vol.
108
, pp.
461
468
.
24.
Rao, S. S., 1996, Engineering Optimization, Theory and Practice, Third Edition, John Wiley & Sons, New York.
25.
Roberts, F. S., 1979, Measurement Theory With Applications to Decision making, Utility, and the Social Sciences, Addison Wesley Publishing Company, Reading, Massachusetts.
26.
Shieh
W.-B.
,
Tsai
L.-W.
,
Azarm
S.
, and
Tits
A. L.
,
1996
, “
Multiobjective Optimization of a Leg Mechanism With Various Spring Configurations for Force Reduction
,”
ASME JOURNAL OF MECHANICAL DESIGN
, Vol.
118
, pp.
179
185
.
27.
Steuer
R. E.
,
1983
, “
An Interactive Weighted Tchebycheff Procedure for Multiple Objective Programming
,”
Mathematical Programming
,
26
, No.
3
, pp.
326
344
.
28.
Steuer, R. E., 1986, Multiple Criteria Optimization, Theory Computation and Applications, John Wiley & Sons, Inc., New York.
29.
Suhir, E., 1987, “Die Attachment Design and Its Influence of Thermal Stresses in Die and the Attachment,” Proceedings of 37th Electronic Components Conference, pp. 508–517.
30.
Vanderplaats, G. N., 1984, Numerical Optimization Techniques for Engineering Design With Applications, McGraw-Hill, New York.
31.
Whitcomb, C. A., Palli N., and Azarm S., 1999, “A Prescriptive Production-Distribution Approach for Decision Making in New Product Design,” IEEE Journal of Systems, Man. and Cybernetics, Vol. 29, Part C, No. 1 (to appear).
32.
Wierzbicki, A. P., 1980, “The Use of Reference Objectives in Multiobjective Optimization,” Multiple Criteria Decision Making and Applications, Edited by Fandel G., Lecture Notes in Economics and Mathematical Systems 177, Springer-Verlag, Berlin, pp. 468–486.
33.
Wilde, D. J., Globally Optimal Design, Wiley, New York, 1978.
34.
Yang, J-B., and Sen P., 1996, “Preference Modeling By Estimating Local Utility Functions for Multiobjective Optimization,” European Journal of Operations Research, No. 22, pp. 115–138.
35.
Yoshimura
M.
,
Hamada
T.
,
Yura
K.
, and
Hitomi
K.
,
1984
, “
Multiobjective Design Optimization of Machine-Tool Spindles
,”
ASME JOURNAL OF MECHANICAL DESIGN
, Vol.
106
, pp.
46
53
.
36.
Yu, P-L., 1985, Multiple Criteria Decision Making, Plenum Press, New York.
37.
Zeleny, M., 1976, “The Theory of the Displaced Ideal,” in Zeleny, M., Multiple Criteria Decision Making, Springer-Verlag, New York.
38.
Zionts
S.
, and
Wallenius
J.
,
1983
, “
An Interactive Multiple Objective Linear Programming Method For A Class Of Underlying Nonlinear Utility Functions
,”
Management Science
, Vol.
29
, No.
5
, pp.
519
529
.
This content is only available via PDF.
You do not currently have access to this content.