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Utility of a Shuffled Differential Evolution algorithm in designing of a Pi-Sigma Neural Network based predictor model [PDF]
Applied Computing and Informatics, 2023 Since the last few decades, Artificial Neural Networks have been the center of attraction of a large number of researchers for solving diversified problem domains.
Rajashree Dash +2 more
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A Stigmergy-Based Differential Evolution
Applied Sciences, 2022 Metaheuristic algorithms are techniques that have been successfully applied to solve complex optimization problems in engineering and science. Many metaheuristic approaches, such as Differential Evolution (DE), use the best individual found so far from ...
Valentín Osuna-Enciso +1 more
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Modular Differential Evolution
Proceedings of the Genetic and Evolutionary Computation Conference, 2023 New contributions in the field of iterative optimisation heuristics are often made in an iterative manner. Novel algorithmic ideas are not proposed in isolation, but usually as an extension of a preexisting algorithm. Although these contributions are often compared to the base algorithm, it is challenging to make fair comparisons between larger sets of
Diederick Vermetten +3 more
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Differential Evolution and Engineering Problems
Mendel, 2023 In this paper, the performance of the Differential Evolution algorithm is evaluated when solving real-world problems. A Set of 13 engineering optimisation problems was selected from the fields of mechanics and industry to illustrate the usability of the
Petr Bujok +2 more
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Improved differential evolution algorithms for solving multi-stage crop planning model in southern region of Thailand [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2019 This paper presents algorithms based on Differential Evolution and Improved Differential Evolution for solving a multistage crop planning problem in southern region of Thailand to maximize the profit.
Phajongjit Pijitbanjong +3 more
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Differential Evolution with DEoptim [PDF]
The R Journal, 2011 The R package DEoptim implements the Differential Evolution algorithm. This algorithm is an evolutionary technique similar to classic genetic algorithms that is useful for the solution of global optimization problems. In this note we provide an introduction to the package and demonstrate its utility for financial applications by solving a non-convex ...
Ardia, David +4 more
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Solving Ordinary Differential Equations With Adaptive Differential Evolution
IEEE Access, 2020 Solving ordinary differential equations (ODEs) is vital in diverse fields. However, it is difficult to obtain the exact analytical solutions of ODEs due to their changeable mathematical forms.
Zijia Zhang, Yaoming Cai, Dongfang Zhang
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Shanghai Jiaotong Daxue xuebao, 2021 In order to improve the flexibility and response efficiency of warehouse dispatching, a cascaded improved differential evolution algorithm is proposed to construct the allocation of goods with the picking trolley running time, shelf stability, and ...
CHEN Guangfeng, YU Lichao
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Parallel differential evolution [PDF]
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753), 2005 Parallel processing has emerged as a key enabling technology in modern computing. Recent software advances have allowed collections of heterogeneous computers to be used as a concurrent computational resource. In this work we explore how differential evolution can be parallelized, using a ring-network topology, so as to improve both the speed and the ...
Dimitris K. Tasoulis +3 more
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Geometric differential evolution [PDF]
Proceedings of the 11th Annual conference on Genetic and evolutionary computation, 2009 Geometric Particle Swarm Optimization (GPSO) is a recently introduced formal generalization of traditional Particle Swarm Optimization (PSO) that applies naturally to both continuous and combinatorial spaces. Differential Evolution (DE) is similar to PSO but it uses different equations governing the motion of the particles.
Alberto Moraglio, Julian Togelius
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