Test results for CEC 2017 (<i>dim</i> = 30).

<div><p>In high-dimensional scenarios, trajectory planning is a challenging and computationally complex optimization task that requires finding the optimal trajectory within a complex domain. Metaheuristic (MH) algorithms provide a practical approach to solving this problem. The Crayfish...

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Bibliographic Details
Main Author:	Yuefeng Leng (20678476) (author)
Other Authors:	Chunlai Cui (20678479) (author), Zhichao Jiang (4724856) (author)
Published:	2025
Subjects:	Science Policy Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified tent chaotic map significantly lower variability orthogonal refracted opposition nonlinear perturbation factor cec2017 test set best competing algorithm optimal trajectory within eight advanced algorithms mh algorithm inspired ecoa &# 8217 dominant dimensional information crayfish optimization algorithm address optimization challenges trajectory planning algorithms provide xlink "> wilcoxon rank search strategies search efficiency results confirm requires finding reducing costs practical verification practical approach population initialization performance comparisons local optima including using enhance diversity dimensional scenarios convergence stability complex domain biological behavior based learning
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Test results for CEC 2017 (<i>dim</i> = 30).

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