Building design optimization plays an important role in maximizing the reliability, cost
efficiency, and environmental sustainability of constructed facilities. As the construction of …

The interaction of bio–geosphere dates to the formation of first unicellular microbes on earth.
However, it is only relatively recently that the complex biological interactions are observed …

This study introduces an effective population-based optimization algorithm, namely the
Golden Search Optimization Algorithm (GSO), for numerical function optimization. The new …

Parameter extraction of photovoltaic (PV) models based on measured current–voltage data
plays an important role in the control, simulation, and optimization of PV systems. Despite …

This paper presents an effective hybrid optimization technique based on a chaotic sine
cosine algorithm (CSCA) and pattern search (PS) for the coordinated design of power …

This paper proposes an improved salp swarm algorithm (ISSA) as an effective metaheuristic
method for tackling global optimization issues and damping power system oscillations. In the …

Kmeans clustering algorithm is an iterative unsupervised learning algorithm that tries to
partition the given dataset into k pre-defined distinct non-overlapping clusters where each …

This article proposes an effective evolutionary hybrid optimization method for identifying
unknown parameters in photovoltaic (PV) models based on the northern goshawk …

In this study, the performances of eight recent swarm intelligence techniques, accelerated
particle swarm optimization (APSO), firefly algorithm, levy-flight krill herd, whale optimization …

Based on the salp swarm algorithm (SSA), this paper proposes an efficient metaheuristic
algorithm for solving global optimization problems and optimizing two commonly …