This research's genesis is in two aspects: first, a guaranteed solution for mitigating the grey
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …

The slime mould algorithm (SMA) is a logical swarm-based stochastic optimizer that is easy
to understand and has a strong optimization capability. However, the SMA is not suitable for …

Although the continuous version of ant colony optimizer (ACOR) has been successfully
applied to various problems, there is room to boost its stability and improve convergence …

Bankruptcy prediction is a crucial application in financial fields to aid in accurate decision
making for business enterprises. Many models may stagnate to low-accuracy results due to …

Moth flame optimization (MFO) is a swarm-based algorithm with mediocre performance and
marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode …

Stochastic optimization has been found in many applications, especially for several local
optima problems, because of their ability to explore and exploit various zones of the feature …

In recent years, a variety of meta-heuristic nature-inspired algorithms have been proposed to
solve complex optimization problems. However, these algorithms suffer from the …

An improved grasshopper optimization algorithm (GOA) is proposed in this paper, termed as
SGOA, which combines simulated annealing (SA) mechanism with the original GOA that is a …

Harris hawks optimization (HHO) is a newly developed swarm-based algorithm and the most
popular optimizer in the recent year, which mimics the cooperation behavior of Harris hawks …

Estimating the photovoltaic model's unknown parameters efficiently and accurately can
determine the solar cell's efficacy in converting the solar energy into electricity. For this …