In this paper, a novel nature-inspired meta-heuristic known as Crested Porcupine Optimizer
(CPO) and inspired by various defensive behaviors of crested porcupine (CP) is proposed …

Controlling and maintaining public health in the face of diseases necessitates the effective
implementation of response strategies, including the distribution of vaccines. By distributing …

The paper addresses the limitations of the Moth-Flame Optimization (MFO) algorithm, a meta-
heuristic used to solve optimization problems. The MFO algorithm, which employs moths' …

Dynamic differential annealed optimization (DDAO) is a recently developed physics-based
metaheuristic technique that mimics the classical simulated annealing mechanism …

If found and treated early, fast-growing skin cancers can dramatically prolong patients' lives.
Dermoscopy is a convenient and reliable tool during the fore-period detection stage of skin …

This paper introduces DGS-SCSO, a novel optimizer derived from Sand Cat Swarm
Optimization (SCSO), aiming to overcome inherent limitations in the original SCSO …

Particle swarm optimization (PSO) suffers from delayed convergence and stagnation in the
local optimal solution, as do most meta-heuristic algorithms. This study proposes a time …

We present a bee foraging behavior-driven mutational salp swarm algorithm (BMSSA)
based on an improved bee foraging strategy and an unscented mutation strategy. The …

Restructuring Particle Swarm Optimization (RPSO) algorithm has been developed as an
intelligent approach based on the linear system theory of particle swarm optimization (PSO) …

The Competitive Swarm Optimizer (CSO) has emerged as a prominent technique for solving
intricate optimization problems by updating only half of the population in each iteration …