Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

This survey is an effort to provide a research repository and a useful reference for
researchers to guide them when planning to develop new Nature-inspired Algorithms …

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 …

An original math-inspired meta-heuristic algorithm, named quadratic interpolation
optimization (QIO), is proposed to address numerical optimization and engineering issues …

Abstract In this paper, Remora Optimization Algorithm (ROA) is proposed, which is a new
bionics-based, natural-inspired, and meta-heuristic algorithm. The inspiration for ROA is …

This paper introduces a new metaheuristic technique known as the Greater Cane Rat
Algorithm (GCRA) for addressing optimization problems. The optimization process of GCRA …

DE algorithms have outstanding performance in solving complex problems. However, they
also have highlighted the need for an effective approach to alleviating the risk of premature …

A novel bio-inspired algorithm called Orca Predation Algorithm (OPA) is proposed in this
paper. OPA simulates the hunting behavior of orcas and abstracts it into several …

In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …

Real-world optimization problems demand an efficient meta-heuristic algorithm which
maintains the diversity of solutions and properly exploits the search space of the problem to …