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Preface

Ying Tan, Yuhui Shi, Xin Yao
2020 Natural Computing  
algorithm which combines two well-known algorithms particle swarm optimization (PSO) and differential evolution (DE).  ...  proposes a new multistage perturbed differential evolution (MPDE).  ... 
doi:10.1007/s11047-020-09803-5 fatcat:you46ta7o5h3pe7t4m5kza3xwi

Magnetic particle swarm optimization

Paulo S. Prampero, Romis Attux
2011 2011 IEEE Symposium on Swarm Intelligence  
The algorithms are applied to a variety of functions and their performance is compared with those of a number of related well-established metaheuristics.  ...  This paradigm gives support to two algorithms that combine elements of the behavior of magnetic dipoles within a framework that includes several elements that are known to be essential to effective multimodal  ...  A more detailed description of the algorithm can be found in [15] , [17] . Differential Evolution The differential evolution (DE) algorithm was developed by Storn and Price in 1995 [18] .  ... 
doi:10.1109/sis.2011.5952575 dblp:conf/swis/PramperoA11 fatcat:52hmngttyjapreudqc53zf5khm

Advances in Recent Nature-Inspired Algorithms for Neural Engineering

Ricardo Soto, Juan A. Gómez-Pulido, Eduardo Rodriguez-Tello, Pedro Isasi
2020 Computational Intelligence and Neuroscience  
, water evaporation optimization, collective decision optimization, interactive search algorithm, vapour-liquid equilibrium metaheuristic, selfish herds algorithm, scattering and repulsive swarm intelligence  ...  In this paper, the authors propose to combine a two-query active learning algorithm with an extreme learning machine (ELM) to solve this problem. e proposed approach is tested on different benchmark datasets  ...  Acknowledgments e guest editors thank all authors who have submitted their manuscripts to this special issue and the reviewers for their hard work with the reviewing process. Ricardo Soto Juan A.  ... 
doi:10.1155/2020/7836239 pmid:33178257 pmcid:PMC7644309 fatcat:vnrmvyl26nd3njwqwt3qfvmxyy

Solving Nonlinear Equations Systems with an Enhanced Reinforcement Learning Based Differential Evolution

Zuowen Liao, Shuijia Li
2022 Complex System Modeling and Simulation  
To deal with NESs efficiently, this study presents an enhanced reinforcement learning based differential evolution with the following major characteristics: (1) the design of state function uses the information  ...  Solving NESs requires the algorithm to locate multiple roots simultaneously.  ...  Differential evolution (DE) is a kind of evolutionary algorithm (EA), which was presented by Storn and Price in 1997 [6] .  ... 
doi:10.23919/csms.2022.0003 fatcat:icogoabzpnht5ljtx5dlmwapvq

Optimal synchronization of Kuramoto oscillators: A dimensional reduction approach

Rafael S. Pinto, Alberto Saa
2015 Physical Review E  
A computationally efficient hill climb rewiring algorithm is proposed to generate networks with optimal synchronization properties.  ...  Our approach can be easily adapted to the case of the Kuramoto models with both attractive and repulsive interactions, and again many recent numerical results can be rederived in a simpler and clearer  ...  In all tests we have performed, our algorithm returned, with little computational effort, networks with greatly enhanced synchronization properties.  ... 
doi:10.1103/physreve.92.062801 pmid:26764738 fatcat:aevzuyztb5ernib2adwn3srywa

Using Differential Evolution to Improve Pheromone-based Coordination of Swarms of Drones for Collaborative Target Detection

Mario G. C. A. Cimino, Alessandro Lazzeri, Gigliola Vaglini
2016 Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods  
., the crossover rate and the differential weight. Then, we compare the performance of our algorithm with three different strategies on six simulated scenarios.  ...  Adaptation is based on the Differential Evolution (DE) and involves the parametric behaviour of both drones and environment.  ...  INTRODUCTION AND MOTIVATION The Differential Evolution algorithm (DE) is a stochastic population based algorithm, very suited for numerical and multi-modal optimization problems.  ... 
doi:10.5220/0005732606050610 dblp:conf/icpram/CiminoLV16 fatcat:7c7tn3x7ejeljdxrmryrh23kgy

Self-Organized Fission-Fusion Control Algorithm for Flocking Systems Based on Intermittent Selective Interaction

Panpan Yang, Maode Yan, Jiacheng Song, Ye Tang
2019 Complexity  
In particular, the trade-off parameter α balances the exploration (fission) and exploitation (fusion) behaviors of flocking system and significantly enhances its movement flexibility and environmental  ...  Numerical simulations demonstrate that the proposed control algorithm can realize the self-organized fission-fusion behavior of flocking system under a unified framework.  ...  the survival and evolution of flocking system.  ... 
doi:10.1155/2019/2187812 fatcat:uuk4o26w4ncktixmuyfrmqmvt4

Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution [article]

Saber Elsayed, Hemant Singh, Essam Debie, Anthony Perry, Benjamin Campbell, Robert Hunjet, Hussein Abbass
2020 arXiv   pre-print
The proposed algorithm is evaluated in obstacle laden environments via simulation with further improvements achieved.  ...  We then argue that given complexity arising from obstacles laden environments, path planning approaches could further enhance this model.  ...  This modified algorithm was then coupled with the differential evolution based path planning algorithm which provided further gains.  ... 
arXiv:2008.12639v1 fatcat:4h7a4zvzjrau3kzjvw4hdufto4

Numerical simulation of trapped dipolar quantum gases: Collapse studies and vortex dynamics

Christof Sparber, Peter Markowich, Zhongyi Huang
2010 Kinetic and Related Models  
We numerically study the three dimensional Gross-Pitaevskii equation for dipolar quantum gases using a time-splitting algorithm.  ...  We are mainly concerned with numerical investigations of the possible blow-up of solutions, i.e. collapse of the condensate, and the dynamics of vortices. 2000 Mathematics Subject Classification.  ...  (a) Figure 3 . 3 Pure repulsive interaction with λ Figure 4 . 4 The behavior of ∇ψ(t, ·) 2 L 2 (R 3 ) vs. time, for λ 1 = λ 2 = 1, n = (0, 0, 1).  ... 
doi:10.3934/krm.2010.3.181 fatcat:5obyhnfngbhc5aumdtbxeqclr4

Top Cited 2018–2019 Papers in the Section "Polymer Theory and Simulation"

Martin Kröger
2020 Polymers  
The most used simulation methods are molecular dynamics, Brownian dynamics, and Monte Carlo, with the only exception being a paper dealing with metamaterials.  ...  The evolution of the fraction of publications falling into one of these fields over the past 50 years is visualized in Figure 1.  ...  Based on these comparisons, they propose a modification to the time marching algorithm. Jehser et al.  ... 
doi:10.3390/polym13010043 pmid:33374327 pmcid:PMC7796158 fatcat:rxqd7dnzdbgd7o4ehobyytwcsy

A Modified Gravitational Search Algorithm for Function Optimization

Shoushuai He, Lei Zhu, Lei Wang, Lu Yu, Changhua Yao
2019 IEEE Access  
In this paper, the concept of repulsive force is introduced and the definition of exponential Kbest is used in a new version of GSA, which is called repulsive GSA with exponential Kbest (EKRGSA).  ...  The proposed algorithm is tested on a set of benchmark functions and compared with other algorithms. The experimental results confirm the high efficiency of EKRGSA.  ...  is changed with the ranges of solution space to enhance the adaptability of the repulsive radius.  ... 
doi:10.1109/access.2018.2889854 fatcat:2tyjco5tazfhzmt2vgcytdz53a

Learning to Score Behaviors for Guided Policy Optimization [article]

Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Anna Choromanska, Krzysztof Choromanski, Michael I. Jordan
2020 arXiv   pre-print
We incorporate these regularizers into two novel on-policy algorithms, Behavior-Guided Policy Gradient and Behavior-Guided Evolution Strategies, which we demonstrate can outperform existing methods in  ...  Combined with smoothed WDs, the dual formulation allows us to devise efficient algorithms that take stochastic gradient descent steps through WD regularizers.  ...  We develop versions of on policy RL algorithms which we call Behavior Guided Policy Gradient (BGPG) and Behavior Guided Evolution Strategies (BGES) that enhance their baseline versions by the use of learned  ... 
arXiv:1906.04349v4 fatcat:xzibkri3efagxov56tpnpcimxq

FDTD Computational Study of Ultra-Narrow TM Non-Paraxial Spatial Soliton Interactions

Z Lubin, J H Greene, A Taflove
2011 IEEE Microwave and Wireless Components Letters  
The work by Aitchison, et al. first reported experimental observations that solitons either repel or attract each other with a periodic evolution over propagation, depending on the relative phase between  ...  Such modifications to enhance its capability have been proposed in [10], [11] .  ...  Such modifications to enhance its capability have been proposed in [10] , [11] .  ... 
doi:10.1109/lmwc.2011.2126019 fatcat:eji5mtwhfrfzhouhzrqvuk7alu

Swarm Filtering Procedure and Application to MRI Mammography

Horia Mihail H. Teodorescu, David J. Malan
2010 POLIBITS Research Journal on Computer Science and Computer Engineering With Applications  
Research on swarming has primarily focused on applying swarming behavior with physics-derived or ad-hoc models to tasks requiring collective intelligence in robotics and optimization.  ...  During the simulations, we adjusted the parameters of the algorithm in order to emphasize the deposits with respect to the surrounding tissue.  ...  We departed from the biological swarming models, that typically use Euclidean distance by using non-Euclidean distance metrics might be valuable for image enhancement using swarm processing algorithms.  ... 
doi:10.17562/pb-42-6 fatcat:2v5hgxsb5ja5bhg7edmsetoh2u

Patch depletion, niche structuring and the evolution of co-operative foraging

Daniel J van der Post, Dirk Semmann
2011 BMC Evolutionary Biology  
We then study the evolution of foraging and grouping behavior in environments with different resource distributions. Results: Our results show that grouping can evolve to increase food intake rates.  ...  Such enhanced patch depletion is particularly apparent on fragmented and partially depleted patches, which are especially difficult for solitary foragers to deplete.  ...  Evolvable behavior Foraging To search for food, individuals have a simple decision making algorithm and a set of behavioral actions Min Max Units Grouping n R (tolerated neighbors) 0.2(15) 0.0 - individuals  ... 
doi:10.1186/1471-2148-11-335 pmid:22093680 pmcid:PMC3306211 fatcat:jptfkw43mzg2bbkxm5yc3recum
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