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1

A review on research trends in using cuckoo search algorithm: applications and open research challenges

Safdar Kalsoom, Abdul Rani Khairul Najmy, Rahim Hasliza A., Rosli Siti Julia, Jamlos Mohd Aminudin

Przegląd Elektrotechniczny

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2023

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R. 99, nr 5

18--24

EN

This paper provides an exclusive understanding of the Cuckoo Search Algorithm (CSA) using a comprehensive review for various optimization problems. CSA is a swarm-based nature inspired, intelligent and metaheuristic approach, which is used to solve complex, single or multi objective optimization problems to provide better solutions with maximum or minimum parameters. It was developed in 2009 by Yang and Deb to emulate the breeding behaviour of cuckoos. Since CSA provides promising solutions to solve real world optimization problems, in recent years there have been introduced several new modified and hybridized CSAs using for different applications. In this regard this article provides a comprehensive survey including recent trends, modifications, open research challenges, applications, and related taxonomies for various optimization problems. The literature of this reviewed paper belongs to the domains of engineering, optimization, and pattern recognition. The aim of this review paper is to provide a detailed overview regarding CSA for possible future directions using the recent contributions.

PL

Ten artykuł zapewnia wyłączne zrozumienie algorytmu przeszukiwania kukułki (CSA) za pomocą kompleksowego przeglądu różnych problemów optymalizacyjnych. CSA to oparte na roju, inteligentne i metaheurystyczne podejście inspirowane naturą, które służy do rozwiązywania złożonych, jedno- lub wielocelowych problemów optymalizacyjnych w celu zapewnienia lepszych rozwiązań z maksymalnymi lub minimalnymi parametrami. Został opracowany w 2009 roku przez Yang i Deb, aby naśladować zachowanie hodowlane kukułek. Ponieważ CSA zapewnia obiecujące rozwiązania do rozwiązywania rzeczywistych problemów optymalizacyjnych, w ostatnich latach wprowadzono kilka nowych zmodyfikowanych i hybrydowych CSA używanych do różnych zastosowań. Pod tym względem ten artykuł zawiera obszerną ankietę, w tym najnowsze trendy, modyfikacje, otwarte wyzwania badawcze, aplikacje i powiązane taksonomie dla różnych problemów optymalizacyjnych. Literatura tego recenzowanego artykułu należy do dziedzin inżynierii, optymalizacji i rozpoznawania wzorców. Celem tego artykułu przeglądowego jest przedstawienie szczegółowego przeglądu dotyczącego CSA dla możliwych przyszłych kierunków z wykorzystaniem ostatnich wkładów.

2

Loadability maximisation in bilateral network for real-time forecasting system using cuckoo search algorithm

Venkatasivanagaraju S., Rao M. Venkateswara

Computer Assisted Methods in Engineering and Science

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2023

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Vol. 30, no. 1

73--88

EN

This manuscript proposes an optimal power flow (OPF) solution in a coordinated bilateralpower network. The primary goal of this project is to maximise the benefits of the powermarket using Newton–Raphson (NR) and cuckoo search algorithm CSA methodologies.The global solution is found using a CSA-based optimisation approach. The study isconducted on real-time bus system. To avoid this, creative techniques have lately beenused to handle the OPF problem, such as loadability maximisation for real-time predictionsystems employing the CSA. In this work, cuckoo search (CS) is used to optimise theobtained parameters that help to minimise parameters in the predecessor and consequentunits of each sub-model. The proposed approach is used to estimate the power load in thelocal area. The constructed models show excellent predicting performance based on derivedperformance. The results confirm the method’s validity. The outcomes are compared withthose obtained by using the NR method. CSA outperformed the other methods in thisinvestigation and gave more accurate predictions. The OPF problem is solved via CSAin this study. Implementing a real-time data case bus system is recommended to test theperformance of the established method in the MATLAB programme.

3

Development of rapid and reliable cuckoo search algorithm for global maximum power point tracking of solar PV systems in partial shading condition

Bentata Khadidja, Mohammedi Ahmed, Benslimane Tarak

Archives of Control Sciences

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2021

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Vol. 31, No. 3

495--526

EN

The solar photovoltaic output power fluctuates according to solar irradiation, temperature, and load impedance variations. Due to the operating point fluctuations, extracting maximum power from the PV generator, already having a low power conversion ratio, becomes very complicated. To reach a maximum power operating point, a maximum power point tracking technique (MPPT) should be used. Under partial shading condition, the nonlinear PV output power curve contains multiple maximum power points with only one global maximum power point (GMPP). Consequently, identifying this global maximum power point is a difficult task and one of the biggest challenges of partially shaded PV systems. The conventional MPPT techniques can easily be trapped in a local maximum instead of detecting the global one. The artificial neural network techniques used to track the GMPP have a major drawback of using huge amount of data covering all operating points of PV system, including different uniform and non-uniform irradiance cases, different temperatures and load impedances. The biological intelligence techniques used to track GMPP, such as grey wolf algorithm and cuckoo search algorithm (CSA), have two main drawbacks; to be trapped in a local MPP if they have not been well tuned and the precision-transient tracking time complex paradox. To deal with these drawbacks, a Distributive Cuckoo Search Algorithm (DCSA) is developed, in this paper, as GMPP tracking technique. Simulation results of the system for different partial shading patterns demonstrated the high precision and rapidity, besides the good reliability of the proposed DCSA-GMPPT technique, compared to the conventional CSA-GMPPT.

4

Failure Correction of a Linear Array of Coupled Parallel Vertical Dipole Antennas

Patidar Hemant, Mahanti Gautam Kumar, Muralidharan R., Singh Prasanna Kumar

Journal of Telecommunications and Information Technology

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2020

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nr 1

62--69

EN

In this paper, a cuckoo search algorithm based on the combined characteristics of the brood parasite behavior and Levy ﬂights is applied to correct the radiation pattern of a linear antenna array composed of parallel dipoles with faulty elements. An eﬀort is made to restore the radiation pattern similar to one without any faulty elements, and the diﬀerence in the values of side lobe level and wide null depth of both patterns, as well as the voltage standing wave ratio obtained from the new voltage excitations become diminished. The examples presented in this paper show the eﬀectiveness of this algorithm in correcting the radiation pattern of a linear array of 36 and 120 dipole antennas with four and ten failed elements, respectively. The results show that the matching condition and the wide null control produced by Cuckoo Search algorithm are more eﬃcient in comparison with the benchmark failure correction algorithm. The approach adopted herein may be applied to other array conﬁgurations as well.