Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimizatio...

Recently, the particle swarm algorithm (PSO) has demonstrated its effectiveness in solving multi-objective optimization problems. However, performance of most existing algorithms depends largely on global or individual best particles. Moreover, due to rapid convergence PSO single objective problems, is prone poorly distributed indicators when dealing with To solve above we propose a competitive...

This paper presents some lens system design and re-engineering experimentations with genetic algorithms and genetic programming. These Evolutionary Algorithms (EA) were successfully applied to a design problem that was previously presented to expert participants of an international lens design conference. Comparative results demonstrate that the use of EA for lens system design is very much hum...

| In this paper the Breeder Genetic Algorithms are compared against both serial and parallel Genetic Algorithms by using a wide range of optimisation functions taken from the literature. The aim is to investigate how the change of the tness function innuences their problem{ solving capabilities. The experimental ndings show that the Breeder Genetic Algorithms outperform the Genetic Algorithms c...

the imperialist competitive algorithm (ica) that was recently introduced has shown its good performance in optimization problems. this algorithm is inspired by competition mechanism among imperialists and colonies, in contrast to evolutionary algorithms. this paper presents optimization of bead geometry in welding process using of ica. therefore, two case studies from literature are presented t...

The hypervolume indicator is one of the most used set-quality indicators for assessment stochastic multiobjective optimizers, as well selection in evolutionary optimization algorithms. Its theoretical properties justify its wide acceptance, particularly strict monotonicity with respect to set dominance which still unique hypervolume-based indicators. This paper discusses computation hypervolume...

blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

using new approaches to optimize the process of power transmission line routing can solve many complex problems which power transmission line routing decision-makers are faced. due to the expansion of involved parameters we can consider multi-objective evolutionary algorithms as appropriate method in this area. in this thesis with using multi-objective evolutionary algorithms nsga-ii and offere...

according to this fact that wind is now a part of global energy portfolio and due to unreliable and discontinuous production of wind energy; prediction of wind power value is proposed as a main necessity. in recent years, various methods have been proposed for wind power prediction. in this paper the prediction structure involves feature selection and use of artificial neural network (ann). in ...

one of the main reasons of unsustainability of city development in iran is that planners and mayors have not almost been able to create connections between different dimensions of a city. sustainability indicators are evaluation tools of cities operation applicable in living environmental, economical, and social aspects. the purpose of this paper is to offer a framework including the descriptio...