Title :
Evolutionary strategies for solving frustrated problems
Author :
Ebeling, Werner ; Rose, Helge ; Schuchhard, Johannes
Author_Institution :
Inst. fur Theor. Phys., Humboldt-Univ., Berlin, Germany
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;
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
DOI :
10.1109/ICEC.1994.350038
