The particle swarm optimization (PSO) method is an instance of a successful application of the philosophy of bounded rationality and decentralized decision making for solving global optimization problems. A number of advantages with respect to other evolutionary algorithms are attributed to PSO making it a prospective candidate for optimum structural design. The PSO-based algorithm is robust an...

The frequency response characteristics of the balanced Surface Acoustic Wave (SAW) filters are governed primarily by their geometrical structures. Therefore, in order to realize desirable frequency response characteristics, the structural design of the balanced SAW filter is formulated as a constrained multi-objective optimization problem. Then a recent Evolutionary Multi-objective Optimization...

This thesis explores novel parameterization concepts for large scale topology optimization that enables the use of evolutionary algorithms in large-scale structural design. Specifically, two novel parameterization concepts based on generative algorithms and Boolean random networks are proposed that facilitate systematic exploration of the design space while limiting the number of design variabl...

Scatter search (SS) and path relinking (PR) are evolutionary methods that have been successfully applied to a wide range of hard optimization problems. The fundamental concepts and principles of the methods were first proposed in the 1970s and 1980s, and were based on formulations, dating back to the 1960s, for combining decision rules and problem constraints. The methods use strategies for sea...

This paper presents a particle swarm optimization algorithm for solving general constrained optimization problems. The proposed approach introduces different methods to update the particle’s information, as well as the use of a double population and a special shake mechanism designed to avoid premature convergence. It also incorporates a simple constraint-handling technique. Twentyfour constrai...

This dissertation investigates methods for the automated design and optimization of laminated composite structures. Optimal design of laminated composite structures is challenging due to the possibility to locally adapt the material system to the mechanical situation. Automated structural design on a computer is enabled by a combination of numerical simulation and optimization algorithms. The f...

The vast use of Linear Prediction Coefficients (LPC) in speech processing systems has intensified the importance of their accurate computation. This paper is concerned with computing LPC coefficients using evolutionary algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Dif-ferential Evolution (DE) and Particle Swarm Optimization with Differentially perturbed Velocity (PSO-DV...

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...

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...