Adjusting the search behaviors of swarm-based algorithms during their execution is a
fundamental errand for addressing real-world global optimizing challenges. Along this line …

Abstract Feature Subset Selection (FSS) is an NP-hard problem to remove redundant and
irrelevant features particularly from medical data, and it can be effectively addressed by …

This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile
Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray …

This paper uses the Butterfly Optimization Algorithm (BOA) with dominated sorting and
crowding distance mechanisms to solve multi-objective optimization problems. There is also …

The COVID-19 is one of the most significant obstacles that humanity is now facing. The use
of computed tomography (CT) images is one method that can be utilized to recognize …

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 …

To address the issues of lacking ability, loss of population diversity, and tendency to fall into
the local extreme value in the later stage of optimization searching, resulting in slow …

This paper proposes a hybrid Enhanced Chimp-Harris Hawks Optimization Algorithm (ECH
3 OA) that combines both enhanced Chimp Optimization algorithm (ChOA) and Harris …

This paper presents a Butterfly Optimization Algorithm (BOA) with a wind-driven mechanism
for avoiding natural enemies known as WDBOA. To further balance the basic BOA …

Particle swarm optimization and genetic algorithms are two classes of popular heuristic
algorithms that are frequently used for solving complex multi-dimensional mathematical …