The optimization problems are becoming more complicated, requiring new and efficient
optimization techniques to solve them. Many bio-inspired meta-heuristic algorithms have …

The aim of this study was to gather, discuss, and compare recently developed
metaheuristics to understand the pace of development in the field of metaheuristics and …

The equilibrium optimizer (EO) is a recently proposed physics-based metaheuristic
algorithm inspired by the dynamic mass balance on a control volume. However, EO may …

A modified adaptive butterfly optimization algorithm is established with the aim of addressing
the “early search blindness” and the relatively poor adaptability of the sensory modality. A …

Grey wolf optimizer (GWO) is a global search algorithm based on grey wolf hunting activity.
However, the traditional GWO is prone to fall into local optimum, affecting the performance of …

As a relatively new model, the artificial bee colony algorithm (ABC) has shown impressive
success in solving optimization problems. Nevertheless, its efficiency is still not satisfactory …

In recent years, Question Answering Systems (QASs) have been known as one of the most
significant tools to access information. QASs are search engines that can return a short and …

Particle filter (PF) is introduced to tackle the limitations of the Kalman filter which adopts
Gaussian in the state and noise of the system. PFs have the problem of sample …

Aiming at the disadvantages of slow convergence and the premature phenomenon of the
butterfly optimization algorithm (BOA), this paper proposes a modified BOA (MBOA) called …

The snow ablation optimizer (SAO) is a meta-heuristic technique used to seek the best
solution for sophisticated problems. In response to the defects in the SAO algorithm, which …