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Biogeography-based optimization (BBO) is a recently-developed algorithm that uses migration to share information among candidate solutions. We use differential evolution algorithm's mutation operator to improve the individual migration operator, and take an adaptive method in setting the value of the scaling factor. The new individual migration is combined with two traditional gene migrations, thus...
The ant colony algorithm (ACA) is a novel simulated evolutionary algorithm which is based on observations to behavior of some ant species. Because of the use of positive feedback mechanism, ACA has stronger robustness, better distributed computer system and easier to combine with other algorithms. However, it also has the flaws, for example mature and halting. This paper presents an optimization algorithm...
The domains ranged by the variables using Web-resources can vary with a time. This is possible even in a runtime of Web-application giving rise to various vulnerabilities and bugs. This paper focuses at the problem mentioned as the individual migration in a problem domain. There is a lack of computational models which operate in an environment of variable domains and the contribution is to develop...
Based on the combination of NSGA-II algorithm and parallel genetic algorithm, this paper presents a parallel genetic algorithm for multi-objective optimization (PNSGA). At the evolving process of this new algorithm, an individual migration to improve the parallel searching speed is applied to improve the efficiency of this algorithm and the accuracy of Pareto optimal set; at the same time, an individual...
A multiobjective evolutionary algorithm based on the parallel evolution of multiple single objective populations and Pareto archive population is proposed. For each single objective population, single objective evolutionary algorithm is applied to optimize separately each of multiobjective functions, where individuals generated by tournament selection from the union of single objective and Pareto...
In the article work of parallel genetic algorithm is described, an idea and types of migration of individuals from one population into another are explained. Factors influencing efficiency of the use of migration are described.
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