In today‟s world, fuzzy logic and particle swarm optimization are used to answer various engineering problems. In this paper, the proportional integral derivative (PID) controller tuning by fuzzy rule method (FRMs) and a particle swarm optimization (PSO) algorithm are proposed to improve controller by adjusting transfer function parameters. The proposed fuzzy rule function and PSO algorithm sea...

This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in a power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer sett...

In this paper, Particle Swarm Optimization (PSO) algorithm and Guaranteed Convergence PSO (GCPSO) are proposed to determine the allocation of Thyristor Controlled Series Compensator (TCSC) and Static Var Compensator (SVC) for maximizing the Total Transfer Capability (TTC) between source and sink area by considering voltage limits and thermal limits in a power system. The optimization is made on...

Group technology (GT) is a useful way to increase productivity with high quality in cellular manufacturing systems (CMSs), in which cell formation (CF) is a key step in the GT philosophy. When boundaries between groups are fuzzy, fuzzy clustering has been successfully adapted to solve the CF problem; however, it may result uneven distribution of parts/machines where the problem becomes larger. ...

Aiming to the problems of slow convergence speed and being easily early-maturing etc. in existing network based on standard particle swarm algorithm, this paper proposes a wireless sensor network coverage optimization algorithm based on the genetic particle swarm optimization (PSO). The wireless sensor maximum coverage is regarded as the objective function, the genetic algorithm with adaptive c...

Particle swarm optimization is a population based optimization technique that is based on probability rules. In this technique each particle moves toward their best individual and group experience had occurred. Fundamental problems of standard PSO algorithm are the falling into the trap of local optimum and its low speed of convergence. One approach for solving the above problems is to combine ...

Particle Swarm Optimization (PSO) is a bioinspired meta-heuristic for solving complex global optimization problems. In standard PSO, the particle swarm frequently gets attracted by suboptimal solutions, causing premature convergence of the algorithm and swarm stagnation. Once the particles have been attracted to a local optimum, they continue the search process within a minuscule region of the ...

This paper presents a Hybrid Particle Swarm Optimization (HPSO) method for solving the Task Assignment Problem (TAP) which is an np-hard problem. Particle Swarm Optimization (PSO) is a recently developed population based heuristic optimization technique. The algorithm has been developed to dynamically schedule heterogeneous tasks on to heterogeneous processors in a distributed setup. Load balan...

This paper mainly discusses the application of the particle swarm optimization in logistics distribution routing problems. Combining with the characteristics of logistics and distribution, it established a mathematical model of the distribution routing problem. Introducing three kinds of optimization strategies in the particle swarm optimization to optimize the particle swarm algorithm, constru...

Particle swarm optimization is affected by premature convergence, no guarantee in finding optimal solution, lack of solution amongst other issues. This paper reviews many literature on PSO and proposes a Hybrid MultiSearch Sub-Swarm PSO by using multiple sub swarm PSO in combination with multi search space algorithm. The particles are divided into equal parts and deployed into the number of sub...