PSO/Snake hybrid algorithm is a merge of particle swarm optimization (PSO), a successful population based optimization technique, and the Snake model, a specialized image processing algorithm. In the PSO/Snake hybrid algorithm each particle in the population represents only a portion of the solution and the population, as a whole, will converge to the final complete solution. In this model ther...

This paper addresses the problem of multiprocessor task-scheduling in a hybrid flow shop (HFS) problem to minimize the makespan. Due to the complex nature of an HFS problem, it is decomposed into the following two sequential decision problems: determining the job permutation in stage 1, followed by a decoding method to assign jobs into each machine in subsequent stages when designing a heuristi...

Particle swarm optimization (PSO) and artificial bee colony (ABC) are new optimization methods that have attracted increasing research interests because of its simplicity and efficiency. However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optimal because of its low global exploration efficiency; ABC algorithm has slower convergence sp...

the gravitational search algorithm (gsa) is a novel optimization methodbased on the law of gravity and mass interactions. it has good ability to search forthe global optimum, but its searching speed is really slow in the last iterations. sothe hybridization of particle swarm optimization (pso) and gsa can resolve theaforementioned problem. in this paper, a modified pso, which the movement ofpar...

Next Generation wireless networks are heterogeneous in nature where a variety of Radio Access Technologies (RATs) coexist in the same coverage area. It is important to select the most appropriate Radio Access Network (RAN) according to the requested service of each user. Hence, this paper proposes a Hybrid Modified Particle Swarm Optimization (PSO) algorithm to select the best access network am...

A new modified severity function is proposed, based on which the N-2 line contingencies in the IEEE 30 bus system are analyzed and ranked. FACTS devices like Static VAR Compensator (SVC) and Thyristor Controlled Series Capacitor (TCSC) are used for achieving reduction in under voltage severity value and reduction in voltage deviation from the nominal value. A hybrid combination of two heuristic...

Particle Swarm Optimization (PSO) is a very popular optimization technique, but it suffers from a major drawback of a possible premature convergence i.e. convergence to a local optimum and not to the global optimum. This paper attempts to improve on the reliability of PSO by addressing the drawback. This problem of premature convergence is more probable with the problems, which have the global ...

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...

M. Balasaraswathi, B. Kalpana ABSTRACT Classification has its roots deep inside the area of prediction and analytics. Performing effective classification can provide huge advantages and improvements in several area. The huge downsides are the unavailability of enhanced techniques and the huge time consumption associated with several machine learning techniques. This paper presents a metaheurist...