Particle swarm optimization (PSO) is an artificial intelligence (AI) technique that can be used to find approximate solutions to extremely difficult or impossible numeric maximization and minimization problems. Particle swarm optimization is an optimization method. It is an optimization algorithm, which is based on swarm intelligence. Optimization problems are widely used in different fields of...

This paper presents an algorithm of particle swarm optimization with reduction for global optimization problems. Particle swarm optimization is an algorithm which refers to the collective motion such as birds or fishes, and a multi-point search algorithm which finds a best solution using multiple particles. Particle swarm optimization is so flexible that it can adapt to a number of optimization...

We propose a new Memetic Particle Swarm Optimization scheme that incorporates local search techniques in the standard Particle Swarm Optimization algorithm, resulting in an efficient and effective optimization method, which is analyzed theoretically. The proposed algorithm is applied to different unconstrained, constrained, minimax and integer programming problems and the obtained results are c...

this paper defines how a meta heuristic search engine called p.s.o can be used to maximize the objective function of a logistic regression model, describing the relationship between the response variable (product designs' score) and a set of explanatory variables (product design factors). at the first phase the processed data, classified and categorized, by kansie engineering is used as input t...

in this paper, a stochastic cell formation problem is studied using queuing theory framework and considering reliability. since cell formation problem is np-hard, two algorithms based on genetic and modified particle swarm optimization (mpso) algorithms are developed to solve the problem. for generating initial solutions in these algorithms, a new heuristic method is developed, which always cre...

one of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. in this regard, there have many models developed, proposing better management in order to maintain water quality. most of these models require input parameters that are either hardly available or time-consuming and expensive to...

in this paper a novel direct adaptive fuzzy system is proposed to control flexible-joints robot including actuator dynamics. the design includes two interior loops: the inner loop controls the motor position using proposed approach while the outer loop controls the joint angle of the robot using a pid control law. one novelty of this paper is the use of a pso algorithm for optimizing the contro...

in this paper we introduce an improvement in the path planning algorithm for the humanoid soccer playing robot which uses ferguson splines and pso (particle swarm optimization). the objective of the algorithm is to find a path through other playing robots to the ball, which should be as short as possible and also safe enough. ferguson splines create preliminary paths using random generated para...

regarding the large number of developed particle swarm optimization (pso) algorithms and the various applications for which pso has been used, selecting the most suitable variant of pso for solving a particular optimization problem is a challenge for most researchers. in this paper, using a comprehensive survey and taxonomy on different types of pso, an expert system (es) is designed to identif...

this paper presents a new nonlinear mathematical model to solve a cell formation problem which assumes that processing time and inter-arrival time of parts are random variables. in this research, cells are defined as a queue system which will be optimized via queuing theory. in this queue system, each machine is assumed as a server and each part as a customer. the grouping of machines and parts...