Throughout the centuries, nature has been a source of inspiration, with much still to learn
from and discover about. Among many others, Swarm Intelligence (SI), a substantial branch …

As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

This paper proposes an efficient optimization algorithm based on the physical phenomenon
of rime-ice, called the RIME. The RIME algorithm implements the exploration and …

In this paper, a novel population-based technique called dung beetle optimizer (DBO)
algorithm is presented, which is inspired by the ball-rolling, dancing, foraging, stealing, and …

Dandelion Optimizer (DO) is a recently proposed swarm intelligence algorithm that
coincides with the process of finding the best reproduction site for dandelion seeds …

In this paper, a new bio-inspired meta-heuristic algorithm, named artificial rabbits
optimization (ARO), is proposed and tested comprehensively. The inspiration of the ARO …

This study proposes a new nature-inspired metaheuristic that mimics the behaviour of the
prairie dogs in their natural habitat called the prairie dog optimization (PDO). The proposed …

In this paper, a novel swarm-based metaheuristic algorithm inspired from the behaviors of
beluga whales, called beluga whale optimization (BWO), is presented to solve optimization …

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 …

This paper proposes a new metaheuristic algorithm called dwarf mongoose optimization
algorithm (DMO) to solve the classical and CEC 2020 benchmark functions and 12 …