Abstract
As was discussed in Section 1.2 the optimal solution to a multiple-objective optimization problem must be nondominated. But, there are likely to be a great many nondominated solutions for a given problem. The choice from among these nondominated solutions is determined by the decision maker’s preferences among the multiple objectives. The goal and compromise programming approaches discussed can be used to specify an a priori functional representation of the decision maker’s preference structure. This functional representation can then be optimized to obtain a single “best” nondominated solution. Goal programming and compromise programming are not the only methods which take this approach but, they do illustrate the general tactic.
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Other Relevant Readings
Graves, S. B., J. L. Ringuest and J. F. Bard, “Recent Developments in Screening Methods for Nondominated Solutions in Multiobjective Optimization,” Computers and Operations Research (forthcoming).
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© 1992 Springer Science+Business Media New York
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Ringuest, J.L. (1992). Decision Making and the Efficient Set. In: Multiobjective Optimization: Behavioral and Computational Considerations. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3612-3_5
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DOI: https://doi.org/10.1007/978-1-4615-3612-3_5
Publisher Name: Springer, Boston, MA
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