scholarly journals A Hybrid Global Optimization Algorithm Based on Particle Swarm Optimization and Gaussian Process

2019 ◽  
Author(s):  
Yan Zhang ◽  
Hongyu Li ◽  
Enhe Bao ◽  
Lu Zhang ◽  
Aiping Yu
Keyword(s):  
Global Optimization ◽  
Particle Swarm Optimization ◽  
Gaussian Process ◽  
Optimization Algorithm ◽  
Particle Swarm ◽  
Global Optimization Algorithm ◽  
Swarm Optimization

Intelligent Optimization of Hybrid Wind/PV/pumped-Storage Power System

2012 ◽  
Vol 512-515 ◽  
pp. 719-722
Author(s):  
Yan Ren ◽  
Yuan Zheng ◽  
Chong Li ◽  
Bing Zhou ◽  
Zhi Hao Mao
Keyword(s):  
Global Optimization ◽  
Particle Swarm Optimization ◽  
Power System ◽  
Hybrid System ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Good Convergence ◽  
Pumped Storage

The hybrid wind/PV/pumped-storage power system was the hybrid system which combined hybrid wind/PV system and pumped-storage power station. System optimization was very important in the system design process. Particle swarm optimization algorithm was a stochastic global optimization algorithm with good convergence and high accuracy, so it was used to optimize the hybrid system in this paper. First, the system reliability model was established. Second, the particle swarm optimization algorithm was used to optimize the system model in Nanjing. Finally, The results were analyzed and discussed. The optimization results showed that the optimal design method of wind/PV/pumped-storage system based on particle swarm optimization could take into account both the local optimization and the global optimization, which has good convergence high precision. The optimal system was that LPSP (loss of power supply probability) was zero.

DE-PSO: A NEW HYBRID META-HEURISTIC FOR SOLVING GLOBAL OPTIMIZATION PROBLEMS

2011 ◽  
Vol 07 (03) ◽  
pp. 363-381 ◽  
Author(s):  
MILLIE PANT ◽  
RADHA THANGARAJ ◽  
AJITH ABRAHAM
Keyword(s):  
Global Optimization ◽  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Real Life ◽  
Test Functions ◽  
Global Optimization Algorithm ◽  
Two Phase ◽  
Swarm Optimization ◽  
Life Problems

This paper presents a simple, hybrid two phase global optimization algorithm called DE-PSO for solving global optimization problems. DE-PSO consists of alternating phases of Differential Evolution (DE) and Particle Swarm Optimization (PSO). The algorithm is designed so as to preserve the strengths of both the algorithms. Empirical results show that the proposed DE-PSO is quite competent for solving the considered test functions as well as real life problems.

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