scholarly journals Parameter optimization of Cuckoo Search Algorithm for Multi Dimensional Function Optimization Problem

2018 ◽  
Vol 7 (18) ◽  
pp. 6-10
Author(s):  
Mohammad Shafiul ◽  
Samiha Sara ◽  
Sanonda Datta ◽  
Jannatun Razia
Keyword(s):  
Parameter Optimization ◽  
Optimization Problem ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Function Optimization

Performances of Adaptive Cuckoo Search Algorithm in Engineering Optimization

2016 ◽  
pp. 676-699 ◽  
Author(s):  
Pauline Ong ◽  
S. Kohshelan
Keyword(s):  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Breeding Strategy ◽  
Function Optimization ◽  
Engineering Optimization ◽  
Optimal Solutions ◽  
Step Size ◽  
Swarm Optimization ◽  
Searching Strategy

A new optimization algorithm, specifically, the cuckoo search algorithm (CSA), which inspired by the unique breeding strategy of cuckoos, has been developed recently. Preliminary studies demonstrated the comparative performances of the CSA as opposed to genetic algorithm and particle swarm optimization, however, with the competitive advantage of employing fewer control parameters. Given enough computation, the CSA is guaranteed to converge to the optimal solutions, albeit the search process associated to the random-walk behavior might be time-consuming. Moreover, the drawback from the fixed step size searching strategy in the inner computation of CSA still remain unsolved. The adaptive cuckoo search algorithm (ACSA), with the effort in the aspect of integrating an adaptive search strategy, was attached in this study. Its beneficial potential are analyzed in the benchmark test function optimization, as well as engineering optimization problem. Results showed that the proposed ACSA improved over the classical CSA.

Bouc-Wen hysteresis parameter optimization for magnetorheological damper using Cuckoo search algorithm

2020 ◽  
Author(s):  
R. Rosli ◽  
M. Z. Mohamed ◽  
G. Priyandoko ◽  
M. F. F. A. Rashid
Keyword(s):  
Parameter Optimization ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Magnetorheological Damper ◽  
Hysteresis Parameter

Solving multi-objective optimization problem using cuckoo search algorithm based on decomposition

2020 ◽  
Vol 51 (1) ◽  
pp. 143-160
Author(s):  
Liang Chen ◽  
Wenyan Gan ◽  
Hongwei Li ◽  
Kai Cheng ◽  
Darong Pan ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective

scholarly journals Optimization of the operation of Dokan hydropower development using Cuckoo Search Algorithm

2022 ◽  
Vol 1216 (1) ◽  
pp. 012016
Author(s):  
K Ahmad-Rashid
Keyword(s):  
Optimization Problem ◽  
Initial Level ◽  
Search Algorithm ◽  
Energy Generation ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Metaheuristic Algorithms ◽  
Hydropower Plant ◽  
Hydropower Development

Abstract In this paper one of the recently developed metaheuristic algorithms, the Cuckoo Search algorithm is used for the optimization of the operation of a large hydropower plant in Kurdistan, Iraq. The optimization problem is to realize an annual planned energy generation with monthly imposed fractions. The obtained results are excellent, nevertheless, there are some limitations of the algorithm determined by the initial level into the reservoir and a certain correlation between the type of the year, the starting level and the planned energy to be realized.

The Cuckoo Search Algorithm Applied to Fuzzy Logic Control Parameter Optimization

2020 ◽  
pp. 175-206
Author(s):  
G. García-Gutiérrez ◽  
D. Arcos-Aviles ◽  
E. V. Carrera ◽  
F. Guinjoan ◽  
A. Ibarra ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Parameter Optimization ◽  
Fuzzy Logic Control ◽  
Control Parameter ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Logic Control

Discrete Non-Integer Order Differentiator Models Using Moth-Flame Optimization Algorithm

2017 ◽  
Vol 261 ◽  
pp. 394-401 ◽  
Author(s):  
Shibendu Mahata ◽  
Suman Kumar Saha ◽  
Rajib Kar ◽  
Durbadal Mandal
Keyword(s):  
Optimization Problem ◽  
Search Algorithm ◽  
Mapping Function ◽  
Cuckoo Search ◽  
Simplex Algorithm ◽  
Cuckoo Search Algorithm ◽  
Optimization Approach ◽  
Integer Order ◽  
Domain Mapping ◽  
Moth Flame Optimization Algorithm

Discrete rational approximation models to the non-integer order differentiator sλ, where λ ε (0, 1), using Moth-Flame Optimization (MFO) algorithm is proposed in this paper. The proposed metaheuristic optimization approach used to design the discrete non-integer order differentiators (DNODs) does not employ any s-to-z domain mapping function to perform the discretization operation. Frequency domain characteristics of DNODs, solution reliability, and algorithm convergence performances are investigated among MFO and an advanced evolutionary algorithm called Particle Swarm Optimization with adaptive inertia weight (PSO-w). Results demonstrate the effectiveness of MFO in outperforming PSO-w in solving this non-linear and multimodal optimization problem. The proposed DNODs also exhibit better performance in comparison with the designs based on techniques such as Nelder-Mead Simplex algorithm and Cuckoo Search Algorithm published in recent literature.

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