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Research on an Improved Differential Evolution Algorithm based on Three Strategies for Solving Complex Function
2015
International Journal of Smart Home
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ability and the stability of optimization, an improved differential evolution algorithm based on multi-population and dynamic local search(MPDLSDE) is proposed in this paper. ...
For the shortcomings of differential evolution algorithm (DE), such as the low convergence rate in the late evolution, easy to trap into the local optimal solution, and weak situation of the global search ...
Differential Evolution Algorithm The DE algorithm is a random search algorithm based on introducing the novel and unique differential mutation operators. ...
doi:10.14257/ijsh.2015.9.11.30
fatcat:pzhf62i2dncgjnz5hho4qv2edm
Differential evolution algorithm of soft island model based on K-means clustering
2020
Indonesian Journal of Electrical Engineering and Computer Science
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<p>Differential evolution (DE) is a highly effective evolutionary algorithm. However, the performance of DE depends on strategies and control parameters. ...
the population implement the same mutation strategies, and dissimilar subpopulations migrate information through the soft island model (SIM). ...
Based on these considerations, a novel DE algorithm, namely the differential evolution algorithm of soft island model based on k-means clustering (KSDE), was proposed. ...
doi:10.11591/ijeecs.v19.i3.pp1548-1555
fatcat:c7tmhjdznjg55dgno2dm6djnka
Analysis of New Distributed Differential Evolution Algorithm with Best Determination Method and Species Evolution
2020
Procedia Computer Science
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This is a new semi-distributed differential evolution algorithm with best determination method and species evolution (DESBS). This algorithm is based on fact-evolution of species around niche. ...
They all are based on the common concept i,e, evolution using selection, mutation, and reproduction. ...
The parameters of strategy operators and size of population affect the performance of differential evolution algorithm. ...
doi:10.1016/j.procs.2020.03.220
fatcat:p3uzetebpbe4xjefw23426igba
Enhanced Success History Adaptive DE for Parameter Optimization of Photovoltaic Models
2021
Complexity
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The less and more greedy mutation strategy is used to enhance the exploitation capability and the exploration capability. ...
To tackle these problems, an enhanced success history adaptive DE with greedy mutation strategy (EBLSHADE) is employed to optimize parameters of PV models to propose a parameter optimization method in ...
[57] proposed an EBLSHADE algorithm based on novel mutation strategy. ...
doi:10.1155/2021/6660115
fatcat:eg3vl472pvc7zairv32nddsydi
Literature Review on Differential Evolution Algorithm
2021
Journal of University of Shanghai for Science and Technology
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Differential evolution algorithm is one of the most efficient metaheuristic approaches. ...
In this paper, a review and analysis is presented in order to help for future research in differential evolution algorithm. ...
Wang et al. (2012) proposed a novel modified binary differential evolution algorithm (NMBDE). ...
doi:10.51201/jusst/21/06471
fatcat:cd4xl66asvdvro3zzbgybhntnm
Control Parameters in Differential Evolution (DE): A Short Review
2018
Robotics & Automation Engineering Journal
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Differential Evolution (DE) is a population based stochastic search algorithm for optimization. DE has three main control parameters, Crossover (cr), Mutation factor (F) and Population size (NP). ...
These control parameters play a vital and crucial rule in improving the performance of search process in DE. This paper introduces a brief review for control parameters in Differential evolution (DE). ...
[6] [7] [8] proposed a novel mutation strategy which is based on the weighted difference between the best and the worst individual during a specific generation, the new mutation strategy is combined ...
doi:10.19080/raej.2018.03.555607
fatcat:hbdk72fkm5bp3bnm6vcnfrffdm
ReDE- A Revised mutation strategy for Differential Evolution Algorithm
2016
International Journal of Intelligent Engineering and Systems
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In this paper, a revised mutation strategy has been implemented. This strategy uses two control parameters and two types of population. ...
Differential Evolution (DE) is considered to be a dominant technique for optimization and is being used to solve various real time problems. ...
Rahnamayan et al. [7] presented a novel algorithm to accelerate differential evolution. This method employs opposition based learning for population initialization and generation jump. ...
doi:10.22266/ijies2016.1231.06
fatcat:jh4wbyrjabbb7benueddbroj7q
Differential Evolution Algorithm with Hierarchical Fair Competition Model
2022
Intelligent Automation and Soft Computing
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HFC model is based on the fair competition of societal system found in natural world. ...
Experimentation has carried out to define the parameter for proposed model on test suit having unimodal problems and multi-model problems. ...
MRDE has the pool of the generation strategies and control parameters. Each individuals utilizes pool based upon the role (task) assigned. ...
doi:10.32604/iasc.2022.023270
fatcat:cua75vvfd5fxnl3poeti6khwzq
Solution of Mixed-Integer Optimization Problems in Bioinformatics with Differential Evolution Method
2021
Mathematics
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Here, a modification is proposed of the differential evolution entirely parallel (DEEP) method introduced recently that was successfully applied to mixed-integer optimization problems. ...
The developed algorithms were implemented in the DEEP software package and applied to three bioinformatic problems. ...
In [26] the authors developed differential evolution with a binary mutation scheme for feature selection. A novel adapted mixed-integer differential evolution algorithm was designed in [27] . ...
doi:10.3390/math9243329
fatcat:4ovnoxyr7rbfvmhbg25lgks77i
Neutral theory based mutation operator for Differential Evolutionary algorithms to enhance population diversity
2019
IOP Conference Series: Materials Science and Engineering
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As an easily used and powerful heuristic search technique based on population, Differential Evolution (DE) algorithm has been widely applied for various global optimization and real engineering problems ...
In order to enhance its performance, we propose a Neutral Mutation (NM) operator for DE algorithm. ...
The authors propose a novel mutation operator based on neutral theory of molecular evolution. ...
doi:10.1088/1757-899x/563/5/052076
fatcat:ypcyjmgnhrgcflvvoti2z3tjne
An Improved Adaptive Differential Evolution based on Hybrid Method for Function Optimization
2016
International Journal of Hybrid Information Technology
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problems, the chaotic optimization algorithm with powerful local searching capacity and multi-strategy are introduced into the DE algorithm in order to propose an improved adaptive differential evolution ...
In order to improve the optimum speed, crease the diversity of the population and overcome the premature convergence problem in differential evolution(DE) algorithm for solving the complex optimization ...
In the IDE, the novel decimal coding is adopted to construct an initial population, some improved differential evolution operators and an integer order criterion based on natural number coding method are ...
doi:10.14257/ijhit.2016.9.3.09
fatcat:e5pis4bq2zcxlplmwzl62ntzne
Adaptive Range Composite Differential Evolution for Fast Optimal Reactive Power Dispatch
2021
IEEE Access
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This paper proposes a novel adaptive range composite differential evolution (ARCoDE) algorithm to efficiently and accurately solve optimal reactive power dispatch (ORPD) problem. ...
Because of a novel adaptive range strategy for control parameters, the proposed ARCoDE possesses superior exploration and exploitation capabilities that can efficiently handle the ORPD problem involving ...
OVERVIEW OF DIFFERENTIAL EVOLUTION The DE algorithm is a stochastic population-based optimization algorithm for real-valued parameters and functions. ...
doi:10.1109/access.2021.3053640
fatcat:hjkm7g7atzgjhdrja567q55vfi
An Adaptive Population Size Differential Evolution with Novel Mutation Strategy for Constrained Optimization
[article]
2018
arXiv
pre-print
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The novel mutation strategy is designed to enhance the effect of status switch based on adaptive population size, which is useful to reduce the constraint violations. ...
Moreover, a mechanism based on multipopulation competition and a more precise method of constraint control are adopted in the proposed algorithm. ...
Zamuda and Brest [17] controlled the population size based on increasing number of FEs, moreover, a set of novel mutation strategies which depend on population size were adopted. ...
arXiv:1805.04217v1
fatcat:wr7fbgbetze6zpt4y2h6vn3b6q
Hybridizing Dragonfly Algorithm with Differential Evolution for Global Optimization
2019
IEICE transactions on information and systems
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Firstly, a novel mutation operator is introduced based on the dragonfly algorithm (DA). ...
To overcome this drawback, a novel hybrid dragonfly algorithm with differential evolution (Hybrid DA-DE) for solving global optimization problems is proposed. ...
Acknowledgements This work is supported by the National Major Scientific Instruments and Equipment Development Project (NO. 2013YQ49087905) and the NSFC and CAAC Joint Conjugal Fund project (NO. ...
doi:10.1587/transinf.2018edp7401
fatcat:qthkq75m2ba3thk3tmnspbbhzq
Recent Trends and Techniques in Image Enhancement using Differential Evolution- A Survey
2017
International Journal of Advanced Research in Computer Science and Software Engineering
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The Differential Evolution algorithm represents an adaptive search process for solving engineering and machine learning optimization problems. ...
Performance of this algorithm rely on its parameter setting. These parameters are usually constant during the entire search space. ...
[10] introduced a new Differential Evolution algorithm based on Adaptive Control Parameters (ACD). ...
doi:10.23956/ijarcsse/v7i4/0108
fatcat:dcz5k3giajabroljggccsjoyae
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