Aparna Duggirala - Academia.edu (original) (raw)
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Genetic algorithms are well known for being expensive optimization tools, especially if the cost ... more Genetic algorithms are well known for being expensive optimization tools, especially if the cost for the analysis of each individual design is high. In the past few years, significant effort has been put forth in addressing the high computational cost GAs. The research conducted in the first part of this thesis continues this effort by implementing new multiple elitist and variable elitist selection schemes for the creation of successive populations in the genetic search process. The new selection schemes allow the GA to take advantage of a greater amount of important genetic information that may be contained in the parent designs, information that is not utilized when using a traditional elitist method selection scheme. By varying the amount of information that may be passed to successive generations from the parent population, the explorative and exploitative characteristics of the GA can be adjusted throughout the genetic search also. The new schemes provided slight reductions in the computational cost of the GA and produced many designs with good fitness' in the final population, while maintaining a high level of reliability.
Genetic algorithms are well known for being expensive optimization tools, especially if the cost ... more Genetic algorithms are well known for being expensive optimization tools, especially if the cost for the analysis of each individual design is high. In the past few years, significant effort has been put forth in addressing the high computational cost GAs. The research conducted in the first part of this thesis continues this effort by implementing new multiple elitist and variable elitist selection schemes for the creation of successive populations in the genetic search process. The new selection schemes allow the GA to take advantage of a greater amount of important genetic information that may be contained in the parent designs, information that is not utilized when using a traditional elitist method selection scheme. By varying the amount of information that may be passed to successive generations from the parent population, the explorative and exploitative characteristics of the GA can be adjusted throughout the genetic search also. The new schemes provided slight reductions in the computational cost of the GA and produced many designs with good fitness' in the final population, while maintaining a high level of reliability.