The optimal reactive power dispatch (ORPD) problem is formulated as a combinatorial optimization problem involving nonlinear objective function with multiple local minima. In this paper, as a new approach, different ant colony optimization (ACO) algorithms are applied to the reactive power dispatch problem. Ant system (AS), the firstly introduced ant colony optimization algorithm, and its direc...

Evolutionary Algorithms (EAs) are population based algorithms, which allow for simultaneous exploration of different parts in the Pareto optimal set. This paper presents Memetic Elitist Pareto Evolutionary Algorithm of Three-Term Backpropagation Network for Classification Problems. This memetic elitist Pareto evolutionary algorithm is called METBP and used to evolve Three-term Backpropagation (...

⎯The convergence of genetic algorithm is mainly determined by its core operation crossover operation. When the objective function is a multiple hump function, traditional genetic algorithms are easily trapped into local optimum, which is called premature convergence. In this paper, we propose a new genetic algorithm with improved arithmetic crossover operation based on gradient method. This cro...

This paper presents a modified optimal control model of drug scheduling in cancer chemotherapy and a new adaptive elitist-population based genetic algorithm (AEGA) to solve it. Working closely with an oncologist, we firstly modify the existing model, because the existing equation of the cumulative drug toxicity is not consistent with the clinical experience and the medicine knowledge. For explo...

Solving multiobjective engineering problems is a very difficult task due to, in general, in these class of problems, the objectives conflict across a high-dimensional problem space. In these problems, there is no single optimal solution, the interaction of multiple objectives gives rise to a set of efficient solutions, known as the Pareto-optimal solutions. During the past decade, Genetic Algor...

A novel framework for automatic articulatory-acoustic feature extraction has been developed for enhancing the accuracy of placeand manner-of-articulation classification in spoken language. The “elitist” approach focuses on frames for which neural network (MLP) classifiers are highly confident, and discards the rest. Using this method, it is possible to achieve a frame-level accuracy of 93% for ...

In this paper, the impacts of elitism rate on the Genetic Algorithm (GA) performance for the Uniform Circular Antenna Array Pattern Synthesis Problem are investigated. For this purpose, a circular antenna array with uniformly spaced isotropic elements having identical excitation amplitudes is used as a model. Unlike the classical GA, we use a GA structure having an elitist population update app...

In this paper, we apply an elitist multi-objective genetic algorithm for solving mechanical component design problems with multiple objectives. Although there exists a number of classical techniques, evolutionary algorithms (EAs) have an edge over the classical methods in that they can find multiple Pareto-optimal solutions in one single simulation run. The proposed algorithm (we call NSGA-II) ...