Game Theory Approach to Engine Performance Optimization ESTECO North America Incorporated

Format:

Conference/Event

Author/Creator:

Fateh, Nader, author.

Conference Name:

SAE World Congress & Exhibition (2008-04-14 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2008

Summary:

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

Notes:

Vendor supplied data

Publisher Number:

2008-01-0871

Access Restriction:

Restricted for use by site license