Remote sensing is defined as a technique for acquiring the information about an object without making physical contact with that image via remote sensors. But the major problem of remotely sensed images is mixed pixel which always degrades the image quality. In this paper we attempted to present an approach for resolving the mixed pixels by using optimization/ Evolutionary algorithm i.e. Biogeo...

This paper presents a novel differential evolution algorithm for optimization of state-of-the-art real world industry challenges. The algorithm includes the self-adaptive jDE algorithm with one of its strongest extensions, population reduction, and is now combined with multiple mutation strategies. The two mutation strategies used are run dependent on the population size, which is reduced with ...

The population diversity is an important issue in evolutionary optimization, playing the main role in exploring the search space. The aim of this paper is to analyze the influence of some diversity enhancing mechanisms on the ability of two algorithms related to evolutionary optimization, differential evolution and particle swarm optimization, to solve static and dynamic optimization problems.

While research on constrained optimization using evolutionary algorithms has been actively pursued, it has had to face the problem that the ability to solve multi-modal problems, which have many local solutions within a feasible region, is insufficient, that the ability to solve problems with equality constraints is inadequate, and that the stability and efficiency of searches is low. We propos...

In this paper, a Differential Evolution (DE) algorithm for solving multiobjective optimization problems to solve the problem of tuning Artificial Neural Network (ANN) parameters is presented. The multiobjective evolutionary used in this study is a Differential Evolution algorithm while ANN used is Three-Term Backpropagation network (TBP). The proposed algorithm, named (MODETBP) utilizes the adv...

Power system operation involves some kind of optimization for ensuring economy, security and stability. Economic load dispatch is one such optimization problems and it is applied for minimizing the total fuel cost. Optimizing the fuel cost is done by properly setting the real power generation from the generators in a power system. Differential evolution is a simple and efficient evolutionary al...

Many real life optimization problems are multimodal. Evolutionary Algorithms (EA) have successfully been applied to solve these problems, but have the disadvantage that converge to only one optimum, even though there are many optima. We proposed a hybrid algorithm combining differential evolution (DE) with tabu search (TS) to solve these problems, allowing to find multiple solutions. The propos...

Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...

This paper investigates a hybrid evolutionary-based design system for automated sizing of analog integrated circuits (ICs). A new algorithm, called competitive co-evolutionary differential evolution (CODE), is proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through el...