A Maglev system was modeled by the exact feedback linearization to achieve two same linear subsystems. The proportional-integral-differential controllers (PID) based on particle swarm optimization (PSO) algorithm with four different inertia weights were then used to regulate both linear subsystems. These different inertia weights were Fixed Inertia Weight (FIW), Linear Descend Inertia Weight (L...

This paper presents three hybrid metaheuristic algorithms that further improve the two hybrid differential evolution (DE) metaheuristic algorithms described in Liao [1]. The three improved algorithms are: (i) MDE′–HJ, which is a modification of MA–MDE′ in Liao [1] by replacing the random walk with direction exploitation local search with the Hooke and Jeeves (HJ) method; (ii) MDE′–IHS–HJ, which...

In this study, a new variant of Particle Swarm Optimization, Electoral Cooperative PSO (ECPSO), is presented and applied into solving the Permutation Flow Shop Scheduling Problem (PFSSP). Firstly, an electoral swarm is generated by the voting of primitive sub-swarms and also participates in evolution of swarm, whose particle candidates come from primitive sub-swarms with variable votes from the...

This paper presents a new optimization algorithm – MCPSO, multi-swarm cooperative particle swarm optimizer, inspired by the phenomenon of symbiosis in natural ecosystems. MCPSO is based on a master–slave model, in which a population consists of one master swarm and several slave swarms. The slave swarms execute a single PSO or its variants independently to maintain the diversity of particles, w...

Delamination is a type of representative damage in composite structures, severely degrading structural integrity and reliability. The identification of delamination is commonly treated as an issue of nondestructive testing. Differing from existing studies, a hybrid optimization algorithm HOA , combining particle swarm optimization PSO with simplex method SM , is proposed to identify delaminatio...

Multilevel thresholding is an important technique for image processing and pattern recognition. The maximum entropy thresholding (MET) has been widely applied in the literature. In this paper, a new multilevel MET algorithm based on the technology of the shuffled frog-leaping (SFLO) algorithm is proposed: called the maximum entropy based shuffled frog-leaping algorithm thresholding (MESFLOT) me...

Linear decreasing inertia weight (LDIW) strategy was introduced to improve on the performance of the original particle swarm optimization (PSO). However, linear decreasing inertia weight PSO (LDIW-PSO) algorithm is known to have the shortcoming of premature convergence in solving complex (multipeak) optimization problems due to lack of enough momentum for particles to do exploitation as the alg...

This paper presents a modification of the particle swarm optimization algorithm (PSO) intended to combat the problem of premature convergence observed in many applications of PSO. In the new algorithm, each particle is attracted towards the best previous positions visited by its neighbors, in addition to the other aspects of particle dynamics in PSO. This is accomplished by using the ratio of t...

Particle swarm optimization (PSO) is a population-based stochastic optimization originating from artificial life and evolutionary computation. PSO is motivated by the social behavior of organisms, such as bird flocking, fish schooling and human social relations. Its properties of low constraint on the continuity of objective function and ability of adapting to the dynamic environment make PSO b...

Many hostile scenarios exist in real-life situations, where cooperation is disfavored and the collective behavior needs intervention for system efficiency improvement. Towards this end, the framework of soft control provides a powerful tool by introducing controllable agents called shills, who are allowed to follow well-designed updating rules for varying missions. Inspired by swarm intelligenc...