Browse Publications Technical Papers 2008-01-0871
2008-04-14

Game Theory Approach to Engine Performance Optimization 2008-01-0871

Genetic Algorithms have proved to be very useful as global search methods for multi-dimensional optimization problems. One drawback, however, is that they are inefficient from the point of view of the number of function evaluations. This paper presents a two phase approach to optimization, using Game Theory in an initial step which provides a family of designs which are close to the Pareto frontier. The starting population for the genetic algorithm is then selected from the non-dominated designs produced in the first phase. This ensures that the genetic algorithm starts with a population of points which are already optimized to a large degree.

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