In this paper, a novel swarm‐based metaheuristic algorithm is proposed, which is called
tuna swarm optimization (TSO). The main inspiration for TSO is based on the cooperative …

This paper introduces a comprehensive survey of a new population-based algorithm so-
called gradient-based optimizer (GBO) and analyzes its major features. GBO considers as …

Optimization techniques, particularly meta-heuristic algorithms, are highly effective in
optimizing and enhancing efficiency across diverse models and systems, renowned for their …

This work presents a new nature-inspired meta-heuristic algorithm named spider wasp
optimization (SWO) algorithm, which is based on replicating the hunting, nesting, and mating …

This paper innovatively proposes the Black Kite Algorithm (BKA), a meta-heuristic
optimization algorithm inspired by the migratory and predatory behavior of the black kite …

In recent years, several metaheuristic algorithms have been introduced in engineering and
scientific fields to address real-life optimization problems. In this study, a novel nature …

Numerous optimization problems can be addressed using metaheuristics instead of
deterministic and heuristic approaches. This study proposes a novel population-based …

This paper proposes a novel population-based optimization method, called Aquila Optimizer
(AO), which is inspired by the Aquila's behaviors in nature during the process of catching the …

This study introduces a novel population-based metaheuristic algorithm called secretary bird
optimization algorithm (SBOA), inspired by the survival behavior of secretary birds in their …

This paper introduces the Human Evolutionary Optimization Algorithm (HEOA), a
metaheuristic algorithm inspired by human evolution. HEOA divides the global search …