A Bio-Inspired Method for Mathematical Optimization Inspired by Arachnida Salticidade

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.

Design of PSO Based Cascaded Multilevel Inverter with Unequal DC Sources

This paper focusing on, the total harmonics distortion (THD) of the output voltage is minimized by the help of a cascade multilevel inverter with non-equal DC sources using particle swarm optimization (PSO) algorithm. The nonlinear transcendental equation that describing the harmonic elimination problem is solved by using many methods existing in literature. In the proposed technique, unequal DC sources are taken for the multilevel inverter, which is practical when different renewable sources are used. The desired switching angles are found out by implementing PSO algorithm which results the minimum THD. Experimental details along with simulation results of 11-level inverter are shown to validate the theory.