• Title/Summary/Keyword: cuckoo search

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Pareto fronts-driven Multi-Objective Cuckoo Search for 5G Network Optimization

  • Wang, Junyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2800-2814
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    • 2020
  • 5G network optimization problem is a challenging optimization problem in the practical engineering applications. In this paper, to tackle this issue, Pareto fronts-driven Multi-Objective Cuckoo Search (PMOCS) is proposed based on Cuckoo Search. Firstly, the original global search manner is upgraded to a new form, which is aimed to strengthening the convergence. Then, the original local search manner is modified to highlight the diversity. To test the overall performance of PMOCS, PMOCS is test on three test suits against several classical comparison methods. Experimental results demonstrate that PMOCS exhibits outstanding performance. Further experiments on the 5G network optimization problem indicates that PMOCS is promising compared with other methods.

Discrete Cuckoo Search based Ontology Alignment Algorithm (이산 Cuckoo Search 기반 온톨로지 정렬 알고리즘)

  • Han, Jun;Jung, Hyunjun;Baik, Doo-Kwon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.664-667
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    • 2014
  • 기존 온톨로지들을 공유 및 재사용하기 위하여 온톨로지 정렬이 연구되고 있다. 기존 정렬 시스템은 온톨로지 데이터 양에 따라 매트릭스를 생성하고 과도한 계산을 통해 처리하여 대용량 데이터 집합에 대하여 공간적 및 계산적으로 부하를 발생하여 효율적이지 않다. 이를 해결하기 위하여 온톨로지 정렬을 휴리스틱 알고리즘을 적용하여 연구 진행하였다. 기존 휴리스틱 알고리즘은 계산이 간단하지만 조율해야 하는 파라미터가 많기에 특정 도메인에 최적 조합이 필요하며 만족한 성능을 얻지 못하였다. 이 논문에서는 Discrete Cuckoo Search(DCS) 기반 온톨로지 정렬 알고리즘을 제안한다. 제안한 알고리즘은 조율해야 하는 파라미터의 개수가 적고 Levy Flight 분포에 따라 탐색하여 계산이 간단하다. 제안된 알고리즘의 성능을 평가하기 위해 OAEI(Ontology Alignment Evaluation Initiative)에서 제공하는 벤치마크 데이터를 사용하여 정확률(Precision)과 재현율(Recall)을 구하고 기존 휴리스틱 정렬 알고리즘과 비교 평가하였다.

An efficient multi-objective cuckoo search algorithm for design optimization

  • Kaveh, A.;Bakhshpoori, T.
    • Advances in Computational Design
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    • v.1 no.1
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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.

Trust Predicated Routing Framework with Optimized Cluster Head Selection using Cuckoo Search Algorithm for MANET

  • Sekhar, J. Chandra;Prasad, Ramineni Sivarama
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.2
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    • pp.115-125
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    • 2015
  • This paper presents a Cuckoo search algorithm to secure adversaries misdirecting multi-hop routing in Mobile ad hoc networks (MANETs) using a robust Trust Predicated Routing Framework with an optimized cluster head selection. The clustering technique designed in this framework leads to efficient routing in MANETs. The heavy work load in the node causes an energy drop in cluster head, which leads to re-clustering of the group, and another cluster head is selected to avoid packet loss during data transmission. The problem in the re-clustering process is that the overall efficiency of the routing process is reduced and the processing time is increased. A Cuckoo search based optimization algorithm is proposed to solve the problem of re-clustering by selecting the secondary cluster head within the initially formed cluster group and eliminating the reclustering process. The proposed framework enables a node to select a reliable and secure route for MANET and the performance can be evaluated by comparing the simulated results with the AODV routing protocol, which shows that the performance of the proposed routing protocol are improved significantly.

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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    • v.16 no.1
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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.

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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    • v.58 no.1
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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.

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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    • v.18 no.2
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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.

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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    • v.19 no.6
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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.

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

  • Lee, Se Jung
    • Korean Journal of Computational Design and Engineering
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    • v.19 no.3
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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.

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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    • v.17 no.5
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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.