Established Evolutionary Search Algorithms

2001 ◽  
pp. 17-44
Author(s):  
Ian C. Parmee
Keyword(s):  
Search Algorithms ◽  
Evolutionary Search

A Review of Genetic Algorithms Applied to Optimizing Maintenance Strategy of Bridges

2011 ◽  
Vol 374-377 ◽  
pp. 2437-2441
Author(s):  
Jing Mei Bian ◽  
Quan Bai ◽  
Qing Hua Shi
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Genetic Algorithms ◽  
Search Algorithms ◽  
Evolutionary Search ◽  
Maintenance Strategy ◽  
Research Focus ◽  
Current State ◽  
Bridge Maintenance ◽  
State Of Research

Abstract:Along with the fast increasing of maintenance demand, the problems associated with maintenance and reinforcement decision-making for deteriorating bridges such as maintenance strategy optimization have been present research focus. The solutions to these problems have inspired a considerable amount of research, one particular area being the application of evolutionary search algorithms such as the genetic algorithm (GA). This paper begins with a brief overview of bridge maintenance strategy optimization followed by a review of the current state of research in applying evolutionary techniques to solving this problem.

scholarly journals Optimal Tuning of Fractional Order Controllers for Dual Active Bridge-Based DC Microgrid Including Voltage Stability Assessment

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1109
Author(s):  
Mohamed Azab ◽  
Alexandre Serrano-Fontova
Keyword(s):  
Power Systems ◽  
Fractional Order ◽  
Voltage Stability ◽  
Optimal Parameter ◽  
Frequency Domain Analysis ◽  
Search Algorithms ◽  
Evolutionary Search ◽  
Dc Microgrid ◽  
Dual Active Bridge ◽  
Pi Controllers

In this article, three evolutionary search algorithms: particle swarm optimization (PSO), simulated annealing (SA) and genetic algorithms (GA), have been employed to determine the optimal parameter values of the fractional-order (FO)-PI controllers implemented in the dual active bridge-based (DAB) DC microgrid. The optimum strategy to obtain the parameters of these FO-PI controllers is still a major challenge for many power systems applications. The FO-PI controllers implemented in the DAB are used to control the DC link voltage to the desired value and limit the current flowing through the converter. Accordingly, the investigated control system has six parameters to be tuned simultaneously; Kp1, Ki1, λ1 for FO-PI voltage controller and Kp2, Ki2, λ2 for FO-PI current controller. Crucially, this tuning optimization process has been developed to enhance the voltage stability of a DC microgrid. By observing the frequency-domain analysis of the closed-loop and the results of the subsequent time-domain simulations, it has been demonstrated that the evolutionary algorithms have provided optimal controller gains, which ensures the voltage stability of the DC microgrid. The main contribution of the article can be considered in the successful application of evolutionary search algorithms to tune the parameters of FO-based dual loop controllers of a DC microgrid scheme whose power conditioner is a DAB topology.

Evolutionary Search Algorithms for Boundary Layer Control

2001 ◽  
pp. 359-366
Author(s):  
W. Maccormack ◽  
O. R. Tutty ◽  
E. Rogers ◽  
P. A. Nelson
Keyword(s):  
Boundary Layer ◽  
Search Algorithms ◽  
Boundary Layer Control ◽  
Evolutionary Search ◽  
Layer Control

The scandium doped boron cluster B27Sc2+: a fruit can-like structure

2019 ◽  
Vol 21 (17) ◽  
pp. 8933-8939 ◽  
Author(s):  
Ehsan Shakerzadeh ◽  
Long Van Duong ◽  
Elham Tahmasebi ◽  
Minh Tho Nguyen
Keyword(s):  
Potential Energy ◽  
Potential Energy Surface ◽  
Energy Surface ◽  
Search Algorithms ◽  
Evolutionary Search ◽  
Boron Cluster ◽  
Systematic Exploration

A systematic exploration of the potential energy surface through evolutionary search algorithms was carried out to identify the most stable B27Sc2+ structure.

scholarly journals An Extension of Geiringer's Theorem for a Wide Class of Evolutionary Search Algorithms.

2006 ◽  
Vol 14 (1) ◽  
pp. 87-118 ◽  
Author(s):  
Boris Mitavskiy ◽  
Jonathan Rowe
Keyword(s):  
Wide Class ◽  
Search Algorithms ◽  
Evolutionary Search
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