In this paper, the behavior of different Particle Swarm Optimization (PSO) variants is analyzed when solving a set of well-known numerical constrained optimization problems. After identifying the most competitive one, some improvements are proposed to this variant regarding the parameter control and the constraint-handling mechanism. Furthermore, the on-line behavior of the improved PSO and som...

Although Particle Swarm Optimizers (PSO) have been successfully used in a wide variety of continuous optimization problems, their use has not been as widespread in discrete optimization problems, particularly when adopting non-binary encodings. In this chapter, we discuss three PSO variants (which are applied on a specific scheduling problem: the Single Machine Total Weighted Tardiness): a Hybr...

Particle Swarm Optimization (PSO) has shown good performance in many optimization problems. However, it easily falls into local optima and suffers from premature convergence on complex multimodal problems. To help trapped particles escape from local minima, a novel hybrid jumps strategy is proposed. The main idea of the new jump strategy is to monitor the changes of previous best particle and t...

We introduce Division of Labor (DoL) from social insects to improve local optimisation of the Particle Swarm Optimiser (PSO). We compared the performance with the basic PSO, a GA and simulated annealing and found improvements around local optima. The PSO with DoL outperforms the basic PSO on most testcases and is comparable in local op-

The interconnected systems is continually increasing in size and extending over whole geographical regions, it is becoming increasingly more difficult to maintain synchronism between various parts of the power system. This paper work presents an advanced adaptive Particle swarm optimization technique to optimize the SVC controller parameters for enhancement of the steady state stability & overc...

This paper constructs fully parallel NN hardware architecture, FPGA has been used to reduce neuron hardware by design the activation function inside the neuron without using lookup table as in most researches, to perform an efficient NN. It consist of two main parts; the first part covers network training using MATLAB program, the second part represents the hardware implementation of the traine...

ةـصلاخلا : ةلاحلا رايعم ثحبلا اذه يف ضرعن – ةلاحلا حشرمُــل لماشلا يبراقتلا تابثلل غارفلا – يمقرلا غارفلا عبشملا يباسحلا ضئافلا مادختساب كلذو ةددحم ةميق اذ . دقو ماظنلل ةديدج ةيصاخ ءاصقتساب رايعملا قُـتشأ ةساردلا ديق . اس رايعم عم رايعملا اذه ةنراقمب انمق امآ جنيسو راآ نم لٍآ لَـبـقِ نم هضرع مت قب . دقو جنيسو راآ رايعم نم لقأ طباوض يذ يلاحلا رايعملا نأ ةنراقملا تنابأ . و نع حرتقملا رايعملا ةعاجن ان...

INNOVATION What is already known about the topic: psoriasis (PsO) is a common skin disease with major impact on quality of life (QoL). Patient-reported data on QoL from large number of PsO patients with and without psoriatic arthritis (PsA) are limited. WHAT THIS STUDY ADDS In a large cohort referred to a university psoriasis center, patients with PsO and concomitant PsA (~30% in this group) ...

Particle swarm optimization (PSO) method is relatively a new population-based intelligence algorithm and exhibits good performance in optimization problems. However, during the optimization process, the particles become more and more similar, and gather into the neighborhood of the best particle in the swarm, which makes the swarm prematurely converged possibly around the local solution. PSO te...