Hybrid multiobjective optimization using modified cuckoo search algorithm in linear array synthesis

Rani, Khairul Najmy Abdul; Malek, Mohd Fareq Abd; Neoh, Siew Chin; Jamlos, Faizal; Affendi, Nur Adyani Mohd; Mohamed, Latifah; Saudin, Norshafinash; Rahim, Hasliza A.

doi:10.1109/lapc.2012.6403005

Cited by 7 publications

(4 citation statements)

References 6 publications

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“…After proving to be efficient and fast and cost-effective for solving single-objective problems, the CS metaheuristic optimization algorithm has been extended to the multiobjective version by Yang and Deb. 29 This version has been used to solve various problems; for further information and a more in-depth analysis of the diverse applications, the reader may refer to Wang et al, 30 Rani et al, 31 and Fister et al 32 The NSCS was developed by He et al 33 According to Deb et al, 25 each solution must be compared to the entire population, in order to determine if it is dominated by another solution. Then, a sorting by fronts is done in the following order: the first front contains the solutions that are nondominated by other solutions.…”

Section: Nscs Algorithmmentioning

confidence: 99%

Coupling of inverse method and cuckoo search algorithm for multiobjective optimization design of an axial flow pump

Chikh

Belaidi

Khelladi

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part A:

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This work describes the application of a multiobjective cuckoo search method for turbomachinery design optimization of an axial pump. Maximization of the total efficiency and minimization of the required net positive suction head of the pump are the two objective functions considered for the optimization problem. The optimization process is carried out on a range of imposed volumetric flow rates, with taking into account at each discretized radius between the hub and tip of the rotor: the profile camber, rotor wall thickness, angular deviation, and the solidity, regarded as geometrical constraints and nominal flow rate as mechanical constraint. Two strategies are proposed in order to solve the problem. In the first one, three forms of mono-objective model with two variables, total efficiency and net positive suction head, are considered. In the second one, a multiobjective model with nondominated sorting scheme is adopted. A comparative evaluation of results obtained from the proposed approach with those of a reference machine and genetic algorithm allowed us to validate the present work.

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Section: Nscs Algorithmmentioning

confidence: 99%

Coupling of inverse method and cuckoo search algorithm for multiobjective optimization design of an axial flow pump

Chikh

Belaidi

Khelladi

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part A:

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“…• Hybrid multiobjective optimization using modified cuckoo search algorithm in linear array synthesis [67].…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

Cuckoo Search: A Brief Literature Review

Fister

Yang²,

Fister

2013

Cuckoo Search and Firefly Algorithm

111

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Cuckoo search (CS) was introduced in 2009, and it has attracted great attention due to its promising efficiency in solving many optimization problems and real-world applications. In the last few years, many papers have been published regarding cuckoo search, and the relevant literature has expanded significantly. This chapter summarizes briefly the majority of the literature about cuckoo search in peer-reviewed journals and conferences found so far. These references can be systematically classified into appropriate categories, which can be used as a basis for further research.Comment: 14 pages 3 figure

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“…The CS algorithm, developed by Yang and Deb in 2009, is one of the most powerful population-based optimization search techniques [38]. Because of its global convergence property [39][40][41][42], the CS has been successfully applied to optimize many real-world engineering design problems, such as wind turbine blades [43], antenna arrays [44][45][46][47][48][49][50][51][52], power systems [53], travelling salesman [54], structural design problems [55], wireless communications [56][57], flow shop scheduling problem [58], job shop scheduling problem [59], model order reduction [60], control systems [61], transmission lines [62], and image processing [63]. The main purpose of this paper is to report a new approach and extend our work in [49][50][51][52][53] and explore the performance of the CS algorithm in the design and optimization of IIR DDs and DIs in comparison with other methods.…”

Section: Introductionmentioning

confidence: 99%

Design and Optimization of Enhanced Magnitude and Phase Response IIR Full-Band Digital Differentiator and Integrator Using the Cuckoo Search Algorithm

Ababneh

Khodier

2022

IEEE Access

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Design of full-band infinite impulse response (IIR) digital differentiator (DD) and digital integrator (DI) based on the L k -norm and the min-max optimality criteria have been demonstrated in literature. However, the designed IIR DDs and DIs using these criteria do not have linear phase or have unsatisfactory magnitude response. In this paper, a novel approach to design, optimize and improve the magnitude response and the linearity of the phase response of IIR DD and DI using the cuckoo search (CS) optimization algorithm is proposed. The proposed approach is based on a varied L k -norm where k linearly increases with the number of the frequency samples between the values 1 and 2. The design and optimization of DDs and DIs are carried out using the CS optimization method due to its simplicity, efficiency, and robustness in solving general multidimensional optimization problems. The performance of the designed DDs and DIs using the proposed approach is compared with designs based on different criteria and algorithms available in literature. The comparison shows that the designed DDs and DIs based on the proposed approach have better phase responses and better or at least comparable magnitude responses compared to those of DDs and DIs designed using other methods in the literature.

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Hybrid multiobjective optimization using modified cuckoo search algorithm in linear array synthesis

Cited by 7 publications

References 6 publications

Coupling of inverse method and cuckoo search algorithm for multiobjective optimization design of an axial flow pump

Coupling of inverse method and cuckoo search algorithm for multiobjective optimization design of an axial flow pump

Cuckoo Search: A Brief Literature Review

Design and Optimization of Enhanced Magnitude and Phase Response IIR Full-Band Digital Differentiator and Integrator Using the Cuckoo Search Algorithm

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