..., enhanced dynamic inertia particle swarm optimization (EDIPSO) algorithm with velocity clamping, to establish all the seven and five constraints of the two-diode model (TDM) and one-diode model (ODM). Design/methodology/approach In complex parameter spaces, the conventional particle swarm optimization...

...Vahid Goodarzimehr; Fereydoon Omidinasab; Nasser Taghizadieh Purpose This paper aims to present a new hybrid algorithm of Particle Swarm Optimization and the Genetic Algorithm (PSOGA) to optimize the space trusses with continuous design variables. The PSOGA is an efficient hybridized algorithm...

..., Figure 2 shows developed CH model. (3) f 2 = 1 n c ∑ r = 1 n c ||D r − B s | | Parameters that are defined mathematically have been modeled as follows: Particle swarm optimization Glowworm swarm optimization Cuckoo search Grasshopper...

... Particle Swarm Optimization and Sine Cosine Algorithm (HPSOSCA), particle swarm optimization (PSO), and sine cosine algorithm (SCA) algorithms. Findings The simulated results on different cases discussed in the dataset section reveal which category of individuals may happen to have the disease...

...Halim Merabti; Khaled Belarbi Purpose Rapid solution methods are still a challenge for difficult optimization problems among them those arising in nonlinear model predictive control. The particle swarm optimization algorithm has shown its potential for the solution of some problems...

... optimization techniques are cuckoo optimization algorithm (COA) and particle swarm optimization (PSO). In this paper, a tight constraint is developed to ensure the less variation in the control input signal and at the same time the overall dynamic performance is not compromised for automatic voltage regulator...