Metaheuristic optimization algorithms (MOAs) are gaining increasing interest because of
their exceptional effectiveness in addressing many optimization issues. Nevertheless, these …

Structural engineering is focused on the safe and efficient design of infrastructure. Projects
can range in size and complexity, many requiring massive amounts of materials and …

This study develops a novel metaheuristic algorithm that is motivated by the behavior of
jellyfish in the ocean and is called artificial Jellyfish Search (JS) optimizer. The simulation of …

In this paper, an efficient new hybrid time series forecasting model combining variational
mode decomposition (VMD) and Deep learning mixed Kernel ELM (MKELM) Autoencoder …

Hybrid heuristic algorithm (HA), an innovative technique in the machine learning field,
enhances the accuracy of reference evapotranspiration (ETo) prediction, which is of …

Solving practical mechanical problems is considered as a real challenge for evaluating the
efficiency of newly developed algorithms. The present article introduces a comparative study …

This paper proposes a hybrid algorithm based on Water Cycle and Moth-Flame Optimization
algorithms for solving numerical and constrained engineering optimization problems. The …

Water cycle algorithm (WCA) is one of the efficient metaheuristic optimization algorithms
inspired by hydrological cycle in nature. WCA can outperform several robust and efficient …

In the real world, there are a number of optimization problems whose search space is
restricted to take binary values; however, there are many continuous metaheuristics with …

This paper proposes an adaptive elitist differential evolution (aeDE) for optimization of truss
structures with discrete design variables. The aeDE algorithm is a newly improved version of …