Now showing items 1-10 of 13
A self-organizing random immigrants genetic algorithm for dynamic optimization problems
In this paper a genetic algorithm is proposed where the worst individual and individuals with indices close to its index are replaced in every generation by randomly generated individuals for dynamic optimization problems. ...
Analyzing evolutionary algorithms for dynamic optimization problems based on the dynamical system.
Artificially inducing environmental changes in evolutionary dynamic optimization
Biological and artificial evolution can be speeded up by environmental changes. From the evolutionary computation perspective, environmental changes during the optimization process generate dynamic optimization problems ...
Evolutionary programming with q-Gaussian mutation for evolutionary optimization problems.
The use of evolutionary programming algorithms with self-adaptation of the mutation distribution for dynamic optimization problems is investigated in this paper. In the proposed method, the q-Gaussian distribution is ...
A framework for inducing artificial changes in optimization problems
Environmental changes are traditionally considered intrinsic in evolutionary dynamic optimization. However, by ignoring that changes can instead be induced, we are ignoring that environmental changes can be eventually ...
Continuous dynamic problem generators for evolutionary algorithms
(IEEE Press, 2007)
Addressing dynamic optimization problems has attracted a growing interest from the evolutionary algorithm community in recent years due to its importance in the applications of evolutionary algorithms in real world problems. ...
Evolution strategies with q-Gaussian mutation for dynamic optimization problems.
Evolution strategies with q-Gaussian mutation, which allows the self-adaptation of the mutation distribution shape, is proposed for dynamic optimization problems in this paper. In the proposed method, a real parameter q, ...
Analysis of fitness landscape modifications in evolutionary dynamic optimization
In this work, discrete dynamic optimization problems (DOPs) are theoretically analysed according to the modifications produced in the fitness landscape during the optimization process. Using the proposed analysis framework, ...
Hyper-selection in dynamic environments.
In recent years, several approaches have been developed for genetic algorithms to enhance their performance in dynamic environments. Among these approaches, one kind of methods is to adapt genetic operators in order for ...
Genetic algorithms with self-organized criticality for dynamic optimization problems
(IEEE Press, 2005)
This paper proposes a genetic algorithm (GA) with random immigrants for dynamic optimization problems where the worst individual and its neighbours are replaced every generation. In this GA, the individuals interact with ...