Convergence of Non{elitist Strategies G Unter Rudolph
ثبت نشده
چکیده
| This paper ooers suucient conditions to prove global convergence of non{elitist evolutionary algorithms. If these conditions can be applied they yield bounds of the convergence rate as a by{product. This is demonstrated by an example that can be calculated exactly. KeyWords| global convergence, non{elitist evolutionary algorithm , martingale theory
منابع مشابه
Convergence of Non-Elitist Strategies
| This paper oers suucient conditions to prove global convergence of non{elitist evolutionary algorithms. If these conditions can be applied they yield bounds of the convergence rate as a by{product. This is demonstrated by an example that can be calculated exactly. KeyWords| global convergence, non{elitist evolutionary algorithm , martingale theory
متن کاملConvergence in evolutionary programs with self-adaptation.
Evolutionary programs are capable of finding good solutions to difficult optimization problems. Previous analysis of their convergence properties has normally assumed the strategy parameters are kept constant, although in practice these parameters are dynamically altered. In this paper, we propose a modified version of the 1/5-success rule for self-adaptation in evolution strategies (ES). Forma...
متن کاملConvergence of Evolutionary Algorithms in General Search Spaces
This paper provides conditions under which evo lutionary algorithms with an elitist selection rule will con verge to the global optimum of some function whose do main may be an arbitrary space These results generalize the previously developed convergence theory for binary and Euclidean search spaces to general search spaces
متن کاملParallel Approaches to Stochastic Global Optimization G Unter Rudolph
In this paper we review parallel implementations of some stochas-tic global optimization methods on MIMD computers. Moreover, we present a new parallel version of an Evolutionary Algorithm for global optimization, where the inherent parallelism can be scaled to obtain a reasonable processor utilization. For this algorithm the convergence to the global optimum with probability one can be assured...
متن کاملEMCSO: An Elitist Multi-Objective Cat Swarm Optimization
This paper introduces a novel multi-objective evolutionary algorithm based on cat swarm optimizationalgorithm (EMCSO) and its application to solve a multi-objective knapsack problem. The multi-objective optimizers try to find the closest solutions to true Pareto front (POF) where it will be achieved by finding the less-crowded non-dominated solutions. The proposed method applies cat swarm optim...
متن کامل