Due to urbanization and the rapid growth of population, carbon emission is increasing,
which leads to climate change and global warming. With an increased level of fossil fuel …

Previous researchers have made impressive strides in developing algorithms and solution
methodologies to address multi-objective optimization (MOO) problems in industrial …

A recent set of overused population-based methods have been published in recent years.
Despite their popularity, most of them have uncertain, immature performance, partially done …

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 …

The optimal design of off-grid hybrid renewable energy systems (HRESs) is a challenging
task, which often involves conflicting goals to be faced. In this work, levelized cost of energy …

Worldwide, the emerging trend of hybrid renewable energy sources integration in modern
power systems is increasing due to privileged prices and clean electricity supply. However …

The optimization problems that must meet more than one objective are called multi-objective
optimization problems and may present several optimal solutions. This manuscript brings …

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 …

Energy transition has brought widespread attentions to the concept of coupled utilization of
the geothermal and solar energy. This paper provides an integrated assessment on …

Image segmentation is an essential pre-processing step and is an indispensable part of
image analysis. This paper proposes Renyi's entropy multi-threshold image segmentation …