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...

The aim of this paper is to propose a new particle swarm optimization algorithm to solve a hybrid flowshop scheduling with sequence-dependent setup times problem, which is of great importance in the industrial context. This algorithm is called diversified particle swarm optimization algorithm which is a generalization of particle swarm optimization algorithm and inspired by an anarchic society ...

In order to overcome the defects of the slow convergence rate of the traditional Genetic Algorithm and basic Particle Swarm Optimization drops into local optimum easily, an improved Particle Swarm Optimization algorithm based on hybrid algorithm is proposed and applied to the signal detection for MIMO-OFDM system. The algorithm optimizes the basic Particle Swarm Optimization algorithm and some ...

Standard particle swarm optimization is easy to fall into local optimum and has the problem of low precision. To solve these problems, the paper proposes an effective approach, called particle swarm optimization based on multiple swarms and opposition-based learning, which divides swarm into two subswarms. The 1st sub-swarm employs PSO evolution model in order to hold the self-learning ability;...

So far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is Particle Swarm Optimization (PSO). Prior some efforts by applying fuzzy logic for improving defects of PSO such as trapping in local optimums and early convergence has been done. Moreover to overcome the problem of i...

in this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. the new method is a hybrid optimization algorithm, which employs the  combination of  the  conventional θ-pso and the shuffled sub-swarms particle optimization (sspso) technique. it is known that the θ-pso algorithm has better optimization performance than standard pso al...

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...

Economic load dispatch is a non linear optimization problem which is of great importance in power systems . While analytical methods suffer from slow conversion and curse of dimensionality particle swarm optimization can be an efficient alternative to solve large scale non linear optimization problem.A lot of advancements have been done to modify this algorithm. This paper presents an overview ...

in this paper a mesh-free model of the functionally graded material (fgm) plate is presented.  the piezoelectric material as a sensor and actuator has been distributed on the top and bottom of the plate, respectively. the formulation of the problem is based on the classical laminated plate theory (clpt) and the principle of virtual displacements. moreover, the particle swarm optimization (pso) ...