• 제목/요약/키워드: Cuckoo Search (CS)

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An efficient multi-objective cuckoo search algorithm for design optimization

  • Kaveh, A.;Bakhshpoori, T.
    • Advances in Computational Design
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    • 제1권1호
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    • pp.87-103
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    • 2016
  • This paper adopts and investigates the non-dominated sorting approach for extending the single-objective Cuckoo Search (CS) into a multi-objective framework. The proposed approach uses an archive composed of primary and secondary population to select and keep the non-dominated solutions at each generation instead of pairwise analogy used in the original Multi-objective Cuckoo Search (MOCS). Our simulations show that such a low computational complexity approach can enrich CS to incorporate multi-objective needs instead of considering multiple eggs for cuckoos used in the original MOCS. The proposed MOCS is tested on a set of multi-objective optimization problems and two well-studied engineering design optimization problems. Compared to MOCS and some other available multi-objective algorithms such as NSGA-II, our approach is found to be competitive while benefiting simplicity. Moreover, the proposed approach is simpler and is capable of finding a wide spread of solutions with good coverage and convergence to true Pareto optimal fronts.

근사 최적화를 활용한 뻐꾸기 탐색법의 성능 개선 (Surrogate-Based Improvement on Cuckoo Search for Global Constrained Optimization)

  • 이세정
    • 한국CDE학회논문집
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    • 제19권3호
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    • pp.245-252
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    • 2014
  • Engineering applications of global optimization techniques are recently abundant in the literature and it may be caused by both new methodologies arising and faster computers coming out. Many of the optimization techniques are based on natural or biological phenomena. This study put focus on enhancing the performace of Cuckoo Search (CS) among them since it has the least number of parameters to tune. The proposed enhancement can be achieved by applying surrogate-based optimization at every cycle of CS, which fortifies the exploitation capability of the original method. The enhanced algorithm has been applied several engineering design problems with constraints. The proposed method shows comparable or superior performance to the original method.

Cuckoo search optimization algorithm for boundary estimation problems in electrical impedance tomography

  • Minho Jeon;Sravan Kumar Konki;Anil Kumar Khambampati;Kyung Youn Kim
    • 전기전자학회논문지
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    • 제28권2호
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    • pp.187-198
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    • 2024
  • Estimating the phase boundary in two-phase flow is crucial for designing and optimizing industrial processes. Electrical impedance tomography (EIT) is a promising technique for imaging phase distribution in such flows. This paper proposes using a cuckoo search (CS) optimization algorithm to estimate the phase boundary with EIT. The boundary is parameterized using the Fourier series, and the coefficients are determined by the CS algorithm. The CS algorithm iteratively seeks the phase boundary configuration by minimizing a cost function. Computer simulations and phantom experiments demonstrate the effectiveness of this method in estimating phase boundaries in two-phase flow.

Subspace search mechanism and cuckoo search algorithm for size optimization of space trusses

  • Kaveh, A.;Bakhshpoori, T.
    • Steel and Composite Structures
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    • 제18권2호
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    • pp.289-303
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    • 2015
  • This study presents a strategy so-called Subspace Search Mechanism (SSM) for reducing the computational time for convergence of population based metaheusristic algorithms. The selected metaheuristic for this study is the Cuckoo Search algorithm (CS) dealing with size optimization of trusses. The complexity of structural optimization problems can be partially due to the presence of high-dimensional design variables. SSM approach aims to reduce dimension of the problem. Design variables are categorized to predefined groups (subspaces). SSM focuses on the multiple use of the metaheuristic at hand for each subspace. Optimizer updates the design variables for each subspace independently. Updating rules require candidate designs evaluation. Each candidate design is the assemblage of responsible set of design variables that define the subspace of interest. SSM is incorporated to the Cuckoo Search algorithm for size optimizing of three small, moderate and large space trusses. Optimization results indicate that SSM enables the CS to work with less number of population (42%), as a result reducing the time of convergence, in exchange for some accuracy (1.5%). It is shown that the loss of accuracy can be lessened with increasing the order of complexity. This suggests its applicability to other algorithms and other complex finite element-based engineering design problems.

Improved Global Maximum Power Point Tracking for Photovoltaic System via Cuckoo Search under Partial Shaded Conditions

  • Shi, Ji-Ying;Xue, Fei;Qin, Zi-Jian;Zhang, Wen;Ling, Le-Tao;Yang, Ting
    • Journal of Power Electronics
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    • 제16권1호
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    • pp.287-296
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    • 2016
  • Conventional maximum power point tracking (MPPT) methods are ineffective under partially shaded conditions because multiple local maximum can be exhibited on power-voltage characteristic curve. This study proposes an improved cuckoo search (ICS) MPPT method after investigating the cuckoo search (CS) algorithm applied in solving multiple MPPT. The algorithm eliminates the random step in the original CS algorithm, and the conception of low-power, high-power, normal and marked zones are introduced. The adaptive step adjustment is also realized according to the different stages of the nest position. This algorithm adopts the large step in low-power and marked zones to reduce search time, and a small step in high-power zone is used to improve search accuracy. Finally, simulation and experiment results indicate that the promoted ICS algorithm can immediately and accurately track the global maximum under partially shaded conditions, and the array output efficiency can be improved.

제조최적화문제 해결을 위한 혼합형 접근법 (Hybrid Approach for Solving Manufacturing Optimization Problems)

  • 윤영수
    • 한국산업정보학회논문지
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    • 제20권6호
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    • pp.57-65
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    • 2015
  • 제조최적화 문제는 비선형 형태의 설계변수로 표시되며, 다양하고 복잡한 제약들을 만족하는 조건하에서 최적해를 구하는 문제이다. 이러한 제조최적화 문제 해결을 위하여 본 연구에서는 혼합형접근법을 제안한다. 제안된 혼합형접근법은 기존의 유전알고리즘(Genetic algorithm: GA)과 쿠쿠탐색(Cuckoo search: CS) 및 언덕오르기법(Hill climbing method: HCM)을 혼합한 형태로 구성된다. 제안된 혼합형접근법에서 GA는 전역적탐색(Global search)를 위해 사용되고, CS는 GA탐색과정에서 발생하는 단점을 개선하기 위해 적용되고, 마지막으로 HCM은 GA와 CS 탐색 이후의 수렴된 지역을 정밀하게 탐색하기 위한 지역적탐색(Local search)을 위해 적용된다. 실험분석에서는 다양한 형태의 제조최적화 문제가 제시되어 본 연구에서 제안된 혼합형접근법와 기존접근법들의 수행도를 각각 비교, 분석하였으며, 그 결과는 본 연구에서 제안한 혼합형접근법의 수행도가 기존접근법들의 수행도보다 더 우수한 것을 확인하였다.

Implementation of Cuckoo Search Optimized Firing Scheme in 5-Level Cascaded H-Bridge Multilevel Inverter for Power Quality Improvement

  • Singla, Deepshikha;Sharma, P.R.
    • Journal of Power Electronics
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    • 제19권6호
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    • pp.1458-1466
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    • 2019
  • Multilevel inverters have appeared as a successful and utilitarian solution in many power applications. The prime objective of an inverter is to keep the fundamental component of the output voltage of a multilevel inverter at a preferred value. Equally important is the need to keep the harmonic components in the output voltage within stated harmonic limits. Therefore, the basis of this research is to develop a harmonic minimization function that optimizes the switching angles of cascaded H-bridge multilevel inverter. Due to benefits of the Cuckoo Search (CS) algorithm, it is applied to determine the switching angles, which are further used to generate the switching pattern for firing the H-bridges of multilevel inverter. Simulation results are compared with SPWM based firing scheme. The switching frequency for SPWM firing scheme is taken as 200 Hz since the switching losses are increased when switching frequency is high. To validate the ability of Cuckoo Search optimized firing scheme in minimization of harmonics, experimental results obtained from hardware prototype of Five Level Cascaded H-Bridge Multilevel Inverter equipped with a FPGA controller are presented to verify the simulation results.

Optimal PID Controller Design for DC Motor Speed Control System with Tracking and Regulating Constrained Optimization via Cuckoo Search

  • Puangdownreong, Deacha
    • Journal of Electrical Engineering and Technology
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    • 제13권1호
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    • pp.460-467
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    • 2018
  • Metaheuristic optimization approach has become the new framework for control synthesis. The main purposes of the control design are command (input) tracking and load (disturbance) regulating. This article proposes an optimal proportional-integral-derivative (PID) controller design for the DC motor speed control system with tracking and regulating constrained optimization by using the cuckoo search (CS), one of the most efficient population-based metaheuristic optimization techniques. The sum-squared error between the referent input and the controlled output is set as the objective function to be minimized. The rise time, the maximum overshoot, settling time and steady-state error are set as inequality constraints for tracking purpose, while the regulating time and the maximum overshoot of load regulation are set as inequality constraints for regulating purpose. Results obtained by the CS will be compared with those obtained by the conventional design method named Ziegler-Nichols (Z-N) tuning rules. From simulation results, it was found that the Z-N provides an impractical PID controller with very high gains, whereas the CS gives an optimal PID controller for DC motor speed control system satisfying the preset tracking and regulating constraints. In addition, the simulation results are confirmed by the experimental ones from the DC motor speed control system developed by analog technology.

Structural damage identification based on modified Cuckoo Search algorithm

  • Xu, H.J.;Liu, J.K.;Lv, Z.R.
    • Structural Engineering and Mechanics
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    • 제58권1호
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    • pp.163-179
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    • 2016
  • The Cuckoo search (CS) algorithm is a simple and efficient global optimization algorithm and it has been applied to figure out large range of real-world optimization problem. In this paper, a new formula is introduced to the discovering probability process to improve the convergence rate and the Tournament Selection Strategy is adopted to enhance global search ability of the certain algorithm. Then an approach for structural damage identification based on modified Cuckoo search (MCS) is presented. Meanwhile, we take frequency residual error and the modal assurance criterion (MAC) as indexes of damage detection in view of the crack damage, and the MCS algorithm is utilized to identifying the structural damage. A simply supported beam and a 31-bar truss are studied as numerical example to illustrate the correctness and efficiency of the propose method. Besides, a laboratory work is also conducted to further verification. Studies show that, the proposed method can judge the damage location and degree of structures more accurately than its counterpart even under measurement noise, which demonstrates the MCS algorithm has a higher damage diagnosis precision.

Optimum design of multi-span composite box girder bridges using Cuckoo Search algorithm

  • Kaveh, A.;Bakhshpoori, T.;Barkhori, M.
    • Steel and Composite Structures
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    • 제17권5호
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    • pp.705-719
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    • 2014
  • Composite steel-concrete box girders are frequently used in bridge construction for their economic and structural advantages. An integrated metaheuristic based optimization procedure is proposed for discrete size optimization of straight multi-span steel box girders with the objective of minimizing the self-weight of girder. The metaheuristic algorithm of choice is the Cuckoo Search (CS) algorithm. The optimum design of a box girder is characterized by geometry, serviceability and ultimate limit states specified by the American Association of State Highway and Transportation Officials (AASHTO). Size optimization of a practical design example investigates the efficiency of this optimization approach and leads to around 15% of saving in material.