dataset-Addressing Maximization Bias in Adaptive Differential Evolution

Description

This data set reports the result of proposed Double Q-learning inspired Differential Evolution Algorithm on the CEC 2021 benchmark test suite. The CEC 2021 benchmark test suite contains 10 benchmark problems of 10 and 20 dimensions with five different parametric configurations, offering a total of 100 problem instances. Ten result tables A1-A10 report the mean and best values of each function on each parametric configuration. The obtained results are compared with other state-of-the-art adaptive DE variants to compare the performance of the proposed DQLiDE algorithm.

Steps to reproduce

Data is obtained by testing the performance of adaptive DE variants and the proposed DQLiDE algorithm on CEC 2021 benchmark test suite.

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