In this paper, we present the use of two evolutionary algorithms to estimate fundamental matrices. We first propose a modification of the Hybrid Taguchi Genetic Algorithm (HTGA) that employs a single objective function, either geometric or algebraic distance, for optimization. We then propose to use a multi-objective optimization algorithm, Intelligent Multi-Objective Evolutionary Algorithm (IM...

In this paper, we propose an approach for detection of anomalies present in medical images. The idea is to combine tow metaphors: Neural Networks (NN) and Evolutionary Algorithm (EA) in a hybrid system. The Radial Basis Function Neural Network (RBF NN) and Multi Population Genetic Algorithm (MPGA) are coupled in one system called neural-evolutionary algorithm. After applying the growing region ...

An improved multi-objective evolutionary algorithm with the hybrid strategies is presented in this paper for multi-objective optimization problems. The evolution process is divided into initial exploration stage, the middle feedback stage and the accelerating convergence stage by the amount of non-dominated individuals in the population. The hybrid strategies and adaptive population structure a...

Handling multi-objective optimization problems using evolutionary computations represents a promising interest area of research, especially the hybrid evolutionary computations. In multi-objective optimization problems the decision maker is interested in determining the set of Pareto-optimal solutions instead of single solution. This paper presents a hybrid evolutionary approach to solve this c...

Sudoku puzzles are an excellent testbed for evolutionary algorithms. The puzzles are accessible enough to be enjoyed by people. However the more complex puzzles require thousands of iterations before a solution is found by an evolutionary algorithm. If we were attempting to compare evolutionary algorithms we could count their iterations to solution as a indicator of relative efficiency. However...

Alopex is a correlation-based algorithm, which shares characteristics of both gradient descent approach and simulated annealing. It has been successfully applied to continuous and combinatorial optimization problems for years. Estimation of Distribution Algorithms (EDAs) is a class of novel evolutionary algorithms (EAs) proposed in recent years. Compared with the traditional EAs, it possesses u...

1 Technological Educational Institute of Kalamata, Greece, e-mail: [email protected] 2 Dept. of Medicine, Democritus University of Thrace, Greece, e-mail: [email protected] 3 Dept. of Computer Engineering & Informatics, University of Patras, Greece, e-mail: [email protected] Abstract. A hybrid evolutionary algorithm that combines genetic programming philosophy, with localized Extended Kalman Filter (E...

This paper presents a new multi-objective coupled energy and reactive power market clearing model namely the MO-CERPMC model in day-ahead competitive market environment. In proposed model, both the active and reactive power markets are considered as coupled markets and cleared in a same time frame. The multi-objective optimization problem involves the minimization of total payment functions for...