首页|A novel adaptive L-SHADE algorithm and its application in UAV swarm resource configuration problem
A novel adaptive L-SHADE algorithm and its application in UAV swarm resource configuration problem
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NSTL
Elsevier
? 2022 Elsevier Inc.In order to further improve the performance of L-SHADE, one of the most competitive variants of differential evolution (DE), a novel adaptive L-SHADE algorithm named AL-SHADE is proposed in the study. Two main parts have been modified for L-SHADE. In one part, a novel mutation strategy current-to-Amean/1 is added to the mutation process to improve the exploitation ability and make full use of population information. In another part, a selection strategy with adaptation scheme for mutation strategies is proposed to tune the exploitation and exploration. The performance of AL-SHADE is evaluated using CEC 2018 and CEC 2014 test suites comparing with L-SHADE, and its state-of-the-art variants, i.e., DbL-SHADE, EB-LSHADE, ELSHADE-SPACMA, jSO, and mL-SHADE. The statistical results demonstrate that AL-SHADE outperforms other competitors in terms of convergence efficiency and accuracy. Finally, AL-SHADE is applied to solve the problem of UAV swarm resource configuration, and the promising performance of AL-SHADE for solving constrained optimization problem are demonstrated by the experimental results. The source code of AL-SHADE can be downloaded from https://github.com/Yintong-Li/AL-SHADE.
Artificial intelligenceCEC 2014 test suiteCEC 2018 test suiteEvolutionary algorithmL-SHADEUAV swarm
Li Y.、Han T.、Zhou H.、Tang S.、Zhao H.
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Aviation Engineering School Air Force Engineering University
NSTL
Elsevier
