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## Tracking Differential Evolution Algorithms: An Adaptive Approach through Multinomial Distribution Tracking with Exponential Forgetting

### Citations

413 |
Differential Evolution: A Practical Approach to Global Optimization
- Price, Storn, et al.
- 2005
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Citation Context ...lation–based stochastic direct search method that utilizes concepts borrowed from the broad class of Evolutionary Algorithms. Several variants of the original DE algorithm have been recently proposed =-=[1,2,3,4,9,10,11,12,14]-=-. Nevertheless, a relatively small number of DE variants have exhibited substantial performance gains in a large number of real-world applications, and hence few variants have attracted the attention ... |

408 | Differential evolution: A simple and efficient adaptive scheme for global optimization over continuous spaces
- Storn, Price
- 1997
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Citation Context ...lation–based stochastic direct search method that utilizes concepts borrowed from the broad class of Evolutionary Algorithms. Several variants of the original DE algorithm have been recently proposed =-=[1,2,3,4,9,10,11,12,14]-=-. Nevertheless, a relatively small number of DE variants have exhibited substantial performance gains in a large number of real-world applications, and hence few variants have attracted the attention ... |

110 |
Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems
- Brest, Greiner, et al.
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Citation Context ...lation–based stochastic direct search method that utilizes concepts borrowed from the broad class of Evolutionary Algorithms. Several variants of the original DE algorithm have been recently proposed =-=[1,2,3,4,9,10,11,12,14]-=-. Nevertheless, a relatively small number of DE variants have exhibited substantial performance gains in a large number of real-world applications, and hence few variants have attracted the attention ... |

107 | Differential evolution algorithm with strategy adaptation for global numerical optimization
- Qin, Huang, et al.
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89 |
Differential evolution: A survey of the state-of-the-art
- Das, Suganthan
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65 |
Oppositionbased differential evolution
- Rahnamayan, Tizhoosh, et al.
- 2008
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65 |
Adaptive differential evolution with optional external archive
- Zhang, Sanderson, et al.
- 2009
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55 | Indentification of time-varying processes - Niedzwiecki - 2000 |

35 | Differential evolution using a neighborhood-based mutation operator
- Das, Abraham, et al.
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Citation Context ...ng equation: θ ML λ i (t) = ni(t) ∑ . (1) K k=1 nk(t) where ni(t) represents the effective window width which can be recursively calculated through the following equation: ni(t) =λni(t − 1) + D i t, =-=(2)-=- for t =1, 2,... and ni(0) = 0, where Di t denotes the number of successes of outcome i at time t. Ifλ = 1 the aforementioned framework corresponds to thesimplecaseofthe θ ML i MLE. Through this fram... |

20 | Adaptive strategy selection in differential evolution
- Gong, Fialho, et al.
- 2010
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Citation Context ... specialized mutation strategies [9], index neighborhood-based mutations [2], or proximity mutations [4]. Variants of the latter type include schemes such as parameter and strategy adaptation schemes =-=[1,5,10,14]-=-. In this study, we borrow ideas from adaptive filter theory to develop an “online” algorithm adaptation technique and incorporate it in the Differential Evolution algorithm. The proposed framework us... |

11 |
Editorial scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems
- Lozano, Molina, et al.
- 2011
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Citation Context ...nctions have been acquired from the recently CEC’2008 Special Session on Large Scale Global Optimization [13]. The remaining four test functions are hybrid composition functions, proposed recently in =-=[6]-=-, and correspond to the f16 − f19 functions of the suite. A detailed description of the benchmark functions can be found in [6,13]. To demonstrate the efficiency of the proposed framework, we compare ... |

6 | Enhancing differential evolution utilizing proximity-based mutation operators
- Epitropakis, Tasoulis, et al.
- 2011
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6 |
Lambda-perceptron: An adaptive classifier for data streams
- Pavlidis, Tasoulis, et al.
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Citation Context ...rlier information should be gradually disregarded. In the current216 M.G. Epitropakis et al. study, we develop a tracking framework that is based on the Recursive Least Squares (RLS) adaptive filter =-=[7,8]-=-. To this end, we incorporate weights to the likelihood function and adopt the framework proposed in [8]. Given that a data sample appears as a signal or a data stream in time, D = {D1,D2,...,Dt,...},... |

2 |
et al. “Benchmark Functions for the CEC’2008 Special Session and Competition on Large Scale Global Optimization
- Tang, Yao, et al.
- 2008
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Citation Context ...h dimensional and scalable benchmark functions with different characteristics. The first six functions have been acquired from the recently CEC’2008 Special Session on Large Scale Global Optimization =-=[13]-=-. The remaining four test functions are hybrid composition functions, proposed recently in [6], and correspond to the f16 − f19 functions of the suite. A detailed description of the benchmark function... |