Evolutionary strategies for solving frustrated problems

Author

Ebeling, Werner ; Rose, Helge ; Schuchhard, Johannes

Author_Institution

Inst. fur Theor. Phys., Humboldt-Univ., Berlin, Germany

fYear

1994

fDate

27-29 Jun 1994

Firstpage

79

Abstract

The main elementary processes and strategies of evolution are investigated and described by simple mathematical models (stochastic networks). Special attention is devoted to Fisher-Eigen type models as well as to Boltzmann-, Darwin- and Haeckel-strategies modelling basic elements of frustrated problems in biological evolution respectively. Several applications of evolutionary strategies to frustrated optimization problems are discussed, in particular the evolution of complex strings satisfying contradictory conditions and the optimization of a network of streets connecting a random distribution of points

Keywords

evolution (biological); genetic algorithms; optimisation; problem solving; biological evolution; evolution; evolutionary strategies; frustrated optimization problems; frustrated problems; optimization; random distribution; stochastic networks; Biological system modeling; Entropy; Evolution (biology); Fluctuations; Genetic mutations; Hydrodynamics; Joining processes; Mathematical model; Stochastic processes; Thermodynamics;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1899-4

Type

conf

DOI

10.1109/ICEC.1994.350038

Filename

350038