The authors applied the particle swarm optimization (PSO) algorithm to solve the conditional nonlinear optimal perturbation (CNOP) and the lower bound of maximum predictable time (LBMPT). The results obtained by the PSO algorithm were compared to those by the traditional optimization algorithm (such as, a gradient descent algorithm based on the adjoint model, ADJ). The authors found that the PS...

Particle swarm optimization (PSO) is a well-known algorithm for global optimization over continuous search spaces. However, this algorithm is limited by the intense conflict between exploration and exploitation search processes. This improper adjustment of exploration and exploitation search processes can introduce an inappropriate level of diversity into the swarm, thereby either decelerating ...

Particle Swarm Optimization (PSO) is a population based optimization technique inspired by the social behaviour of bird flocking [1]. This algorithm has been successfully used for beam dynamics simulations due to its excellent capability to deal with large-dimensional optimization problems [2, 3]. At the MLS and BESSY II PSO was first successfully applied to improve the lifetime by 20 ~ 30% wit...

SI is a computational and collective behavioral metaphor that is used for solving problems. The problems can be solved by SI by taking ants, termites, bees and wasps as an example. The application of SI algorithm are ACO, PSO and ABC which have been already applied to solve real world optimization problems in engineering. ACO is a member of SI in which ACO is inspired by the behaviour of ant co...

Particle swarm optimization (PSO) is an artificial intelligence (AI) technique that can be used to find approximate solutions to extremely difficult or impossible numeric maximization and minimization problems. Particle swarm optimization is an optimization method. It is an optimization algorithm, which is based on swarm intelligence. Optimization problems are widely used in different fields of...

In this paper, use of Differential Evolution (DE) based and Particle swarm optimization (PSO) based algorithm for the allocation & coordinated operation of multiple FACTS (Flexible AC Transmission System) devices for the improved power transfer capacity and economic operation of an interconnected power system is presented. Both the DE and PSO based approach is applied on IEEE 30-bus system. The...

Cloud Computing is subscription-based service which is used to obtain storage space on network and computer resources. The cloud makes it possible to access information from anywhere at any time. Cloud provides both software and hardware necessary to run various applications according to the needs of the user. To fulfil those needs of user internet connection is required to access the cloud. In...

The aim of this research is to design a PID Controller using particle swarm optimization (PSO) algorithm for multiple-input multiple output (MIMO) Takagi-Sugeno fuzzy model. The conventional gain tuning of PID controller (such as Ziegler-Nichols (ZN) method) usually produces a big overshoot, and therefore modern heuristics approach such as PSO are employed to enhance the capability of tradition...

global optimization methods play an important role to solve many real-world problems. flower pollination algorithm (fp) is a new nature-inspired algorithm, based on the characteristics of flowering plants. in this paper, a new hybrid optimization method called hybrid flower pollination algorithm (fppso) is proposed. the method combines the standard flower pollination algorithm (fp) with the par...

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...