The objective of this paper is to demonstrate the application of genetic algorithms to the engine technology selection process. The “technology identification, evaluation, and selection” method is discussed in conjunction with genetic algorithm optimization as a technique to quickly evaluate the impact of various technologies and select the subset with the highest potential payoff. Techniques used to model various aspects of engine technologies are described, with emphasis on technology constraints and their impact on the combinatorial optimization of technologies. Challenges include objective function formulation and development of models to deal with incompatibilities among different technologies. Typical results are presented for an 80-technology optimization using various visualization techniques to assist in easy interpretation of genetic algorithm results. Finally, several ideas for future development of these methods are briefly explored.

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