Cuckoo search algorithm based on frog leaping local search and chaos theory

Liu, Xueying; Fu, Meiling

doi:10.1016/j.amc.2015.06.041

Cited by 32 publications

(14 citation statements)

References 12 publications

(17 reference statements)

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“…Section 3.1 illustrates the benefits of logistic map. Most of modified CS algorithms are mainly focused on choosing chaotic maps (e.g., [23][24][25]). These studies do not mention how to reduce repeated calculation in each dimension.…”

Section: Simulation Experimentsmentioning

confidence: 99%

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Modified Cuckoo Search Algorithm with Variational Parameters and Logistic Map

Liu

Wang

et al. 2018

Algorithms

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Cuckoo Search (CS) is a Meta-heuristic method, which exhibits several advantages such as easier to application and fewer tuning parameters. However, it has proven to very easily fall into local optimal solutions and has a slow rate of convergence. Therefore, we propose Modified cuckoo search algorithm with variational parameter and logistic map (VLCS) to ameliorate these defects. To balance the exploitation and exploration of the VLCS algorithm, we not only use the coefficient function to change step size α and probability of detection p a at next generation, but also use logistic map of each dimension to initialize host nest location and update the location of host nest beyond the boundary. With fifteen benchmark functions, the simulations demonstrate that the VLCS algorithm can over come the disadvantages of the CS algorithm.In addition, the VLCS algorithm is good at dealing with high dimension problems and low dimension problems.

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Section: Simulation Experimentsmentioning

confidence: 99%

“…Huang et al [24] proposed a Chaos-enhanced cuckoo search that use logistic map to ameliorate CS. Liu and Fu [25] proposed a cuckoo search algorithm based on frog leaping local search and chaos theory. Zheng and Zhou [26] used Gaussian distribution to initiate the CS algorithm, which only considered the initial part was not comprehensive.…”

Section: Introductionmentioning

confidence: 99%

Modified Cuckoo Search Algorithm with Variational Parameters and Logistic Map

Liu

Wang

et al. 2018

Algorithms

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“…e chaos theory is a mathematics researching field which is applied to enhance the random search process. Many studies have integrated chaos theory into different algorithms to improve the effectiveness of metaheuristic algorithms in solving optimization problems such as the PSO algorithm [23], SA [24], Cuckoo Search Algorithm (CSA) [25], Fruit-fly Optimization (FFO) algorithm [26], ABC algorithm [27], and Differential Evolution (DE) [28]. In general, these methods with the integration of chaos theory have offered a higher solution quality than original methods.…”

Section: Introductionmentioning

confidence: 99%

Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using Chaotic Stochastic Fractal Search Algorithm

Anh

2020

Complexity

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This paper proposes a chaotic stochastic fractal search algorithm (CSFSA) method to solve the reconfiguration problem for minimizing the power loss and improving the voltage profile in distribution systems. The proposed method is a metaheuristic method developed for overcoming the weaknesses of the conventional SFSA with two processes of diffuse and update. In the first process, new points will be created from the initial points by the Gaussian walk. For the second one, SFSA will update better positions for the particles obtained in the diffusion process. In addition, this study has also integrated the chaos theory to improve the SFSA diffusion process as well as increase the rate of convergence and the ability to find the optimal solution. The effectiveness of the proposed CSFSA has been verified on the 33-bus, 84-bus, 119-bus, and 136-bus distribution systems. The obtained results from the test cases by CSFSA have been verified to those from other natural methods in the literature. The result comparison has indicated that the proposed method is more effective than many other methods for the test systems in terms of power loss reduction and voltage profile improvement. Therefore, the proposed CSFSA can be a very promising potential method for solving the reconfiguration problem in distribution systems.

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“…Li Huang [11] improved three parts of the standard CS algorithm, i.e., chaotic initial position, variable step size of Lévy Flight,and chaos transboundary treatment. Liu Xiaoying [12] introduced the inertia weight factor of the particle swarm algorithm into the Levy flight, and adopted the leapfrog algorithm in the local search mechanism of the standard CS algorithm. Seen in the light of No Free Lunch Theorem [13], any existing optimization strategy can hardly solve all kinds of problems.…”

Section: Introductionmentioning

confidence: 99%

Enhancing the Performance of Cuckoo Search Algorithm with Multi-Learning Strategies

Huang

Zheng

Ding

et al. 2019

IEICE Trans. Inf. & Syst.

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The Cuckoo Search (CS) is apt to be trapped in local optimum relating to complex target functions. This drawback has been recognized as the bottleneck of its widespread use. This paper, with the purpose of improving CS, puts forward a Cuckoo Search algorithm featuring Multi-Learning Strategies (LSCS). In LSCS, the Converted Learning Module, which features the Comprehensive Learning Strategy and Optimal Learning Strategy, tries to make a coordinated cooperation between exploration and exploitation, and the switching in this part is decided by the transition probability P c. When the nest fails to be renewed after m iterations, the Elite Learning Perturbation Module provides extra diversity for the current nest, and it can avoid stagnation. The Boundary Handling Approach adjusted by Gauss map is utilized to reset the location of nest beyond the boundary. The proposed algorithm is evaluated by two different tests: Test Group A(ten simple unimodal and multimodal functions) and Test Group B(the CEC2013 test suite). Experiments results show that LSCS demonstrates significant advantages in terms of convergence speed and optimization capability in solving complex problems.

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Cuckoo search algorithm based on frog leaping local search and chaos theory

Cited by 32 publications

References 12 publications

Modified Cuckoo Search Algorithm with Variational Parameters and Logistic Map

Modified Cuckoo Search Algorithm with Variational Parameters and Logistic Map

Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using Chaotic Stochastic Fractal Search Algorithm

Enhancing the Performance of Cuckoo Search Algorithm with Multi-Learning Strategies

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