Abstract— Particle Swarm Optimization (PSO) algorithm is swarm intelligence based algorithm which is used for solving optimization problem. PSO simulates the intelligent foraging behavior of a flock of birds. This paper presents a modification in PSO and develops an algorithm called Highly Convergent Particle Swarm Optimization (HCPSO) algorithm, in which the velocity of particle is made to be ...

In this paper we investigate the application of the Particle Swarm Optimization (PSO) technique for solving the Hardware/Software partitioning problem. The PSO is attractive for the Hardware/Software partitioning problem as it offers reasonable coverage of the design space together with O(n) main loop's execution time, where n is the number of proposed solutions that will evolve to provide the ...

Particle swarm optimization (PSO) has undergone many changes since its introduction in 1995. Being a stochastic algorithm, PSO and its randomness present formidable challenge for the theoretical analysis of it, and few of the existing PSO improvements have make an effort to eliminate the random coefficients in the PSO updating formula. This paper analyzes the importance of the randomness in the...

This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is classical proportional integral (PI) controller. In contrast, second one based on adaptive neuro-fuzzy inference systems (proportional integral-adaptive system (PI-ANFIS) and particle swarm optimization-proportional (PSO-PI-ANFIS)). objective regul...

A new optimization algorithm is proposed, since a huge problem that many algorithms faced was not being able to effectively balance the global and local search ability. Matter exists in three states: solid, liquid, gas, which presents different motion characteristics. Inspired by multi- states of matter, individuals have characteristics could present The Finite Element Analysis (FEA) approach c...

The liquid cargo replenishment decision based on ship’s stability, strength and the floating state is a multiobjective optimization problem. The mathematical model of multi-objective is built in this paper. Aiming to obtain the feasible solution, the adaptive step ergodic of permutation and combination is applied in terms of the cargo oil tank and the water ballast tank. particle swarm optimiza...

This paper proposes an enhanced Particle Swarm Optimization (PSO) algorithm in order to deal with the issue that time and cost of PSO is quite high when scheduling workflow tasks a cloud computing environment. To reduce particle dimensions ensure initial quality, intensive are combined tasks. Next, initialization optimized better quality reduced search space. Then, suitable self-adaptive functi...

The paper presents a Field Programmable Gate Array (FPGA) based tracker to accurately track the maximum power point (MPP) of a photovoltaic (PV) array. The tracking logic realized on FPGA is based on a modified version of Adaptive Perceptive Particle Swarm Optimization (APPSO) technique. Photovoltaic generation systems use MPP tracker because the photovoltaic array exhibits multiple maxima in t...