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- W4200482246 abstract "This paper proposes a new meta-heuristic called Jumping Spider Optimization Algorithm (JSOA), inspired by Arachnida Salticidae hunting habits. The proposed algorithm mimics the behavior of spiders in nature and mathematically models its hunting strategies: search, persecution, and jumping skills to get the prey. These strategies provide a fine balance between exploitation and exploration over the solution search space and solve global optimization problems. JSOA is tested with 20 well-known testbench mathematical problems taken from the literature. Further studies include the tuning of a Proportional-Integral-Derivative (PID) controller, the Selective harmonic elimination problem, and a few real-world single objective bound-constrained numerical optimization problems taken from CEC 2020. Additionally, the JSOA’s performance is tested against several well-known bio-inspired algorithms taken from the literature. The statistical results show that the proposed algorithm outperforms recent literature algorithms and is capable to solve challenging real-world problems with unknown search space." @default.
- W4200482246 created "2021-12-31" @default.
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- W4200482246 date "2021-12-29" @default.
- W4200482246 modified "2023-10-18" @default.
- W4200482246 title "A Bio-Inspired Method for Mathematical Optimization Inspired by Arachnida Salticidade" @default.
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- W4200482246 doi "https://doi.org/10.3390/math10010102" @default.
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