Adaptive learning techniques for design decision making
Date
1996
Authors
Vuppala, Mangaraju
Major Professor
Advisor
Schmerr, Lester W.
Committee Member
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Abstract
In this work a combination of a general regression neural network and genetic algorithms is used to implement a new approach to multiobjective design. This new approach will offer several significant advantages over previous methods. The Pareto optimal solutions generated by the various multiobjective optimization methods can be different from each other. Therefore, the quality of a solution concept or procedure is not just a function of how well the method obtains a particular solution but instead may be defined on the basis of other attributes such as the mathematical basis of the method, its generality, and the efficiency of its calculation.
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thesis