Coupling of immune algorithms and game theory in multiobjective optimization

Abstract

Multiobjective optimization problems have been solved in recent years by several researchers using different kind of algorithms, among them genetic and evolutionary algorithms and artificial immune systems. The results obtained during these tests were satisfactory, but these researchers observed that there still is a need for new ideas for algorithms which will increase efficiency and at the same time decrease the computational effort. In this paper the idea of coupling of immune algorithms with game theory is presented. The authors take out the most important elements from the artificial immune system, such as clonal selection and suppression, and couple them with the idea of Nash equilibrium. The new approach and some preliminary tests and results are presented here. © 2010 Springer-Verlag.