PSO is a population-based technique for optimization, which simulates the social behavior of the fish schooling or bird flocking. Two significant weaknesses of this method are: first, falling into local optimum and second, the curse of dimensionality. In this work we present the FCPSO-H to overcome these weaknesses. Our approach was implemented in the cooperative PSO, which employs fuzzy logic ...

Travelling Sales Person Problem is one of the classical combinatorial optimization problems that belong to the NP-complete class. It is the problem of finding the optimized path for a given set of cities. The path is drawn in such a way that the salesperson has to visit each city exactly once. This paper provides an efficient method for solving the classical Travelling Sales Person Problem by u...

Particle Swarm Optimization (PSO) is a metaheuristic optimization algorithm that owes much of its allure to its simplicity and its high effectiveness in solving sophisticated optimization problems. However, since the performance of the standard PSO is prone to being trapped in local extrema, abundant variants of PSO have been proposed by far. For instance, Fuzzy Adaptive PSO (FAPSO) algorithms ...

MAV (Micro Aerial Vehicle) is nonlinear plant, it is difficult to obtain stable control for MAV attitude due to uncertainties. The purpose of this paper is to propose one robust 、 stable control strategy for MAV to accommodate system uncertainties, variations, and external disturbances. In this paper, an interval type II fuzzy sliding-mode controller combined with PSO algorithm (ITIIFSMC-PSO) i...

In this paper, a comparison among Particle swarm optimization (PSO), Bee Colony Optimization (BCO) and the Bat Algorithm (BA) is presented. In addition, a modification to the main parameters of each algorithm through an interval type-2 fuzzy logic system is presented. The main aim of using interval type-2 fuzzy systems is providing dynamic parameter adaptation to the algorithms. These algorithm...

-The performance of fuzzy logic (FLC) and PID controllers optimized by particle swarm optimization (PSO) for semi-active suspension system using magneto-rheological (MR) damper are investigated. MR damper is an intelligent damper filled with particle magnetic polarizable and suspended into a liquid form. The Bouc-Wen model of MR damper is used to determine the required damping force based on fo...

The catfish particle swarm optimization (CatfishPSO) algorithm is a novel swarm intelligence optimization technique. This algorithm was inspired by the interactive behavior of sardines and catfish. The observed catfish effect is applied to improve the performance of particle swarm optimization (PSO). In this paper, we propose fuzzy CatfishPSO (F-CatfishPSO), which uses fuzzy to dynamically chan...

Particle Swarm Optimization is a population based optimization technique that based on probability rules. In this technique each particle moves toward their best individual and group experience had occurred. Fundamental problems of a standard PSO algorithm are fall into local optimum trap and the low speed of the convergence. One of the methods to solve these problems is to combine PSO algorith...

This work aims at proposing a robust strategy to determine the optimal operating parameters based on fuzzy modeling for enhancing productivity of methane using Pelvetia canaliculata. The applied is combination logic (FL) and particle swarm optimizer (PSO). First, FL used build model that describes production experimental datasets. Second, PSO algorithm obtain best-operating conditions process. ...