Personal Best Position Particle Swarm Optimization
نویسنده
چکیده
In this paper, a new particle swarm optimization method has been proposed. In the proposed approach a novel philosophy of modifying the velocity update equation of Standard Particle Swarm Optimization approach has been used. The modification has been done by vanishing the gbest term in the velocity update equation of SPSO. The performance of the proposed algorithm (Personal Best Position Particle Swarm Optimization, PBPPSO) has been tested on several benchmark problems. It is concluded that the PBPPSO performs better than SPSO in terms of accuracy and quality of solution.
منابع مشابه
One Half Global Best Position Particle Swarm Optimization Algorithm
In this paper, a new particle swarm optimization algorithm have been proposed. The algorithm is named as One Half Personal Best Position Particle Swarm Optimizations (OHGBPPSO) and a novel philosophy by modifying the velocity update equation has been presented. The performance of algorithm has been tested through numerical and graphical results. The results obtained are compared with the standa...
متن کاملSolving two-dimensional packing problem using particle swarm optimization
Particle swarm optimization is one of the evolutionary computations which is inspired by social behavior of bird flocking or fish schooling. This research focuses on the application of the particle swarm optimization to two-dimensional packing problem. Packing problem is a class of optimization problems which involve attempting to pack the items together inside a container, as densely as possib...
متن کاملImproved PSO-based Static RWA Solver Avoiding Premature Convergence
In this paper an improved Particle Swarm Optimization (PSO) scheme is proposed to solve Static Routing and Wavelength Assignment (static RWA) where the movement of the swarm particles is influenced by their personal-best position searched so far and the position of the global-best particle. Simulation results show that the proposed scheme performs better in terms of particle fitness value and a...
متن کاملImproved Particle Swarm Optimization with a Collective Local Unimodal Search for Continuous Optimization Problems
A new local search technique is proposed and used to improve the performance of particle swarm optimization algorithms by addressing the problem of premature convergence. In the proposed local search technique, a potential particle position in the solution search space is collectively constructed by a number of randomly selected particles in the swarm. The number of times the selection is made ...
متن کاملGaussian Particle Swarm Optimization with Differential Evolution Mutation
During the past decade, the particle swarm optimization (PSO) with various versions showed competitiveness on the constrained optimization problems. In this paper, an improved Gaussian particle swarm optimization algorithm (GPSO) is proposed to improve the diversity and local search ability of the population. A mutation operator based on differential evolution (DE) is designed and employed to u...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012