Convergence Track Based Adaptive Differential Evolution Algorithm (CTbADE)
نویسندگان
چکیده
One of the challenging problems with evolutionary computing algorithms is to maintain balance between exploration and exploitation capability in order search global optima. A novel convergence track based adaptive differential evolution (CTbADE) algorithm presented this research paper. The crossover rate mutation probability parameters a have significant role searching more diverse population improves helps escape from local optima problem. Tracking path over time enhance speed for varying problems. An powerful parameter-controlled sequences utilized learning period-based memory following are introduced proposed will be helpful maintaining equilibrium an algorithm's capability. comprehensive test suite standard benchmark different natures, i.e., unimodal/multimodal separable/non-separable, was used power CTbADE algorithm. Experimental results show performance terms average fitness, solution quality, when compared few other commonly state-of-the-art algorithms, such as jDE, CoDE, EPSDE algorithms. This prove addition literature solve real optimize computational models high number adjust during problem-solving process.
منابع مشابه
Developing Adaptive Differential Evolution as a New Evolutionary Algorithm, Application in Optimization of Chemical Processes
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ژورنال
عنوان ژورنال: Computers, materials & continua
سال: 2022
ISSN: ['1546-2218', '1546-2226']
DOI: https://doi.org/10.32604/cmc.2022.024211