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Applied Soft Computing, 2020
The optimization performance of differential evolution(DE) algorithm significantly depends on control parameters and mutation strategy. However, it is difficult to set suitable control parameters and select reasonable mutation strategy for DE in solving ...
Wu Deng +3 more
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The optimization performance of differential evolution(DE) algorithm significantly depends on control parameters and mutation strategy. However, it is difficult to set suitable control parameters and select reasonable mutation strategy for DE in solving ...
Wu Deng +3 more
semanticscholar +1 more source
A constrained differential evolution algorithm to solve UAV path planning in disaster scenarios
Knowledge-Based Systems, 2020Disasters have caused significant losses to humans in the past decades. It is essential to learn about the disaster situation so that rescue works can be conducted as soon as possible.
Xiaobing Yu, Chenliang Li, JiaFang Zhou
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Multiobjective Differential Evolution and Differential Evolution for Irrigation Planning
World Environmental and Water Resources Congress 2009, 2009The present paper discusses the applicability of Multiobjective Differential Evolution (MODE) and single objective Differential Evolution (DE) to a case study of Mahi Bajaj Sagar Project, Rajasthan, India. Three objectives, namely, net benefits, agricultural production and labour employment are analyzed in the multiobjective framework using MODE.
Piyush Gupta +2 more
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Differential Evolution: A survey of theoretical analyses
Swarm and Evolutionary Computation, 2019Differential Evolution (DE) is a state-of-the art global optimization technique. Considerable research effort has been made to improve this algorithm and apply it to a variety of practical problems.
K. Opara, J. Arabas
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IEEE Transactions on Cybernetics, 2020
In contrast to the traditional single-tasking evolutionary algorithms, evolutionary multitasking (EMT) travels in the search space of multiple optimization tasks simultaneously.
Zhengping Liang +4 more
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In contrast to the traditional single-tasking evolutionary algorithms, evolutionary multitasking (EMT) travels in the search space of multiple optimization tasks simultaneously.
Zhengping Liang +4 more
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Differential Evolution: An Overview
2016Differential evolution (DE) is one of the most influential optimization algorithms up-to-date. DE works through analogous computational steps as used by a standard evolutionary algorithm. Nevertheless, not like traditional Evolutionary Algorithms, the DE-variants agitate the current generation populace members with the scaled differences of ...
Amritpal Singh, Sushil Kumar 0005
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Parameter Selection of Differential Evolution by another Differential Evolution Algorithm
2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), 2019The performance of differential evolution (DE) highly depends on its control parameters, especially for the first proposed simple or standard DE. Control parameters suitable for one objective function are generally not beneficial to another. To automatically find out optimal control parameter settings for different objective functions, we propose a ...
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Optimal power flow by means of improved adaptive differential evolution
, 2020Optimal power flow (OPF) problem is a large-scale, non-convex, multi-modal, and non-linear constrained optimization problem, which has been widely used in power system operation.
Shuijia Li +4 more
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An improved differential evolution algorithm and its application in optimization problem
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2021Wu Deng +5 more
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Recombining angles in Differential Evolution
2009 IEEE Congress on Evolutionary Computation, 2009In this paper we wish to investigate how optimization problems involving angles can best be handled when using Differential Evolution (DE) as the optimization technique. Specifically we state the hypothesis that angles should not be recombined naivly.
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