Harmony Search Based Parameter Ensemble Adaptation for Differential Evolution by Rammohan Mallipeddi

“…In differential evolution (DE) algorithm, depending on the characteristics of the problem at hand and the available computational resources, different strategies combined with a different set of parameters may be effective. …”
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Differential Evolution with Novel Mutation and Adaptive Crossover Strategies for Solving Large Scale Global Optimization Problems by Ali Wagdy Mohamed, Abdulaziz S. Almazyad

“…This paper presents Differential Evolution algorithm for solving high-dimensional optimization problems over continuous space. …”
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Improved Parallel Differential Evolution Algorithm with Small Population for Multi-Period Optimal Dispatch Problem of Microgrids by Tianle Li, Yifei Li, Fang Wang, Cheng Gong, Jingrui Zhang, Hao Ma

“…In the new approach, the main population of the parallel algorithm is divided into several small populations, and each performs the original operators of a differential evolution algorithm, i.e., mutation, crossover, and selection, in different processes concurrently. …”
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A two phase differential evolution algorithm with perturbation and covariance matrix for PEMFC parameter estimation challenges by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe

“…In this study, a novel algorithm PCM-DE, based on the Differential Evolution framework, is proposed. …”
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Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

“…Seven different experimental data sets are used to improve the performance of the proposed differential evolution with an integrated mutation per iteration algorithm (DEIMA). …”
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An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

“…At the bottom level of the hyper-heuristic algorithm, this paper uses the particle swarm optimization algorithm, grey wolf optimization algorithm, differential evolution algorithm, and positive cosine optimization algorithm as the basic operators. …”
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State information-driven surrogate-assisted differential evolution for computationally expensive constrained optimization problems by Zihua Zhu, Zan Yang, Zhiyong Liu, Liming Chen, Xiwen Cai

“…Abstract In this paper, a state information-driven surrogate-assisted differential evolution called SI-SADE is proposed for solving expensive constrained optimization problems, in which both the population state and adaptive search mechanism are respectively evaluated and designed based on the feasibility and state information. …”
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AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

“…Results Simulation results demonstrate that the ISSA significantly outperforms the original SSA and other state-of-the-art algorithms, such as particle swarm optimization (PSO), differential evolution (DE), artificial bee colony (ABC), and whale optimization algorithm (WOA). …”
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Global progress in competitive co-evolution: a systematic comparison of alternative methods by Stefano Nolfi, Paolo Pagliuca

“…The usage of broad sets of training data is paramount to evolve adaptive agents. In this respect, competitive co-evolution is a widespread technique in which the coexistence of different learning agents fosters adaptation, which in turn makes agents experience continuously varying environmental conditions. …”
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Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization by Serdar Ekinci, Davut Izci, Veysel Gider, Laith Abualigah, Mohit Bajaj, Ievgen Zaitsev

“…To ensure optimal performance, the parameters of the RPIDD2 controller are optimized using metaheuristic algorithms, including the flood optimization algorithm (FLA), reptile search algorithm (RSA), particle swarm optimization (PSO) and differential evolution (DE). …”
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A Comparison of Inversion Methods for Surrogate‐Based Groundwater Contamination Source Identification With Varying Degrees of Model Complexity by Zhenbo Chang, Zhilin Guo, Kewei Chen, Zibo Wang, Yang Zhan, Wenxi Lu, Chunmiao Zheng

“…Each method has its own advantages and disadvantages under specific site conditions. To evaluate the applicability of these methods, we chose one representative inversion algorithm from each category, namely the Improved Butterfly Optimization Algorithm (IBOA) for simulation optimization, the Ensemble Smoother with Multiple Data Assimilation (ES‐MDA) for data assimilation, and the DiffeRential Evolution Adaptive Metropolis with a Snooker Update and Sampling from a Past Archive (DREAM(ZS)) for Bayesian inference. …”
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Prediction of Drifter Trajectory Using Evolutionary Computation by Yong-Wook Nam, Yong-Hyuk Kim

“…The evolutionary methods Differential Evolution (DE), Particle Swarm Optimization (PSO), Covariance Matrix Adaptation Evolution Strategy (CMA-ES), and ensembles of the above were used, with the DE&PSO ensemble found to be the best prediction model. …”
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Peningkatan Akurasi Metode Weighted Fuzzy Time Series Forecasting Menggunakan Algoritma Evolusi Differensial dan Fuzzy C-Means by Agus Fachrur Rozy, Solimun Solimun, Ni Wayan Surya Wardhani

“…There are two commonly applied approaches: the Differential Evolution (DE) algorithm and Fuzzy C-Means (FCM). …”
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