The optimal placement of distributed generation (DG) is a critical task for distribution companies in order to keep the distribution network running smoothly. The optimal placement of DG units is an optimization problem. In this paper, minimization o...
As one of the most promising forms of renewable energy, solar energy is increasingly deployed. The simulation and control of photovoltaic (PV) systems requires identification of their parameters. A Hybrid Adaptive algorithm based on JAYA and Differen...
Active distribution networks (ADNs) require battery energy storage system (BESS) scheduling strategies that reduce operating costs while preserving electrical feasibility and battery lifetime. This paper proposes a parallel adapted JAYA-based methodo...
Metaheuristic algorithms have become essential tools for solving complex, high-dimensional, and constrained optimization problems. This paper introduces an adaptive R implementation of the parameter-free Jaya algorithm, enhanced with methodological i...
Tugboats are indispensable for ensuring the safe and efficient berthing and unberthing of large vessels, and their scheduling policies have a direct impact on port efficiency and operating costs. To overcome the limitations of conventional single-obj...
The optimal design of steel frame structures subjected to natural frequency constraints is a challenging problem due to its highly nonlinear and computationally demanding nature. In this study, Parameter-Free Jaya Algorithm (PFJA) is proposed for the...
A major problem in power systems is achieving a match between the load demand and generation demand, where security, dependability, and quality are critical factors that need to be provided to power producers. This paper proposes a proportional&ndash...
This study explores the application of JAYA optimization algorithms to significantly enhance the performance of indoor optical wireless communication (OWC) systems. By strategically optimizing photo-signal parameters, the system was able to improve s...
This study develops a novel Lyrebird Optimization Algorithm (LOA), a technique inspired by the wild behavioral strategies of lyrebirds in response to potential threats. In a two-area interconnected power system that includes non-reheat thermal statio...
The growing use of electrical and electronic appliances, coupled with shorter product lifespans, has accelerated the rise in waste electrical and electronic equipment (WEEE). Accurate forecasting is essential for addressing environmental challenges,...
The grey wolf optimization (GWO) algorithm is widely utilized in many global optimization applications. In this paper, a dynamic opposite learning-assisted grey wolf optimizer (DOLGWO) was proposed to improve the search ability. Herein, a dynamic opp...
In order to identify the parameters of photovoltaic (PV) cells and modules more accurately, reliably and efficiently, a chaotic second order oscillation JAYA algorithm (CSOOJAYA) is proposed. Firstly, both logical chaotic map and the mutation strateg...
In rail transit traction, synchronous reluctance machines (SynRMs) are potential alternatives to traditional AC motors due to their energy-saving and low-cost characteristics. However, the nonlinearities of SynRMs are more severe than permanent magne...
The Energy-Efficient Hybrid Flow Shop Scheduling Problem poses a significant multi-objective optimization challenge, necessitating the simultaneous minimization of conflicting objectives: Total Tardiness, Total Energy Cost, and Carbon Trading Cost. T...
24 September 2025
Accurate gender identification from written text is critical for author profiling, recommendation systems, and demographic analytics in digital ecosystems. This study introduces a scalable framework for gender classification in Turkish, combining con...
There are many factors that affect the shear capacity of FRP (fiber-reinforced polymer)-strengthened reinforced concrete (RC) beams, and traditional capacity models based on empirical or semi-empirical formulas often suffer from insufficient accuracy...
A reasonable dataset, which is an essential factor of renewable energy forecasting model development, sometimes is not directly available. Waiting for a substantial amount of training data creates a delay for a model to participate in the electricity...
In the optimum design of reinforced concrete (RC) structural members, the robustness of the employed method is important as well as solving the optimization problem. In some cases where the algorithm parameters are defined as non-effective values, lo...
This paper proposes an improved Harris Hawks Optimization (IHHO) algorithm to enhance maximum power point tracking (MPPT) performance in photovoltaic (PV) systems operating under various conditions. The IHHO introduces Tent chaotic mapping to improve...
A growing number of researchers are interested in deploying unmanned surface vehicles (USVs) in support of ocean environmental monitoring. To accomplish these missions efficiently, multiple-waypoint path planning strategies for survey USVs are still...
Grouting power is a vital parameter that can be used as an indicator for simultaneously controlling grouting pressure and injection rate. Accurate grouting power prediction contributes to the real-time optimization of the grouting process, guaranteei...
Renewable energy (RE) resources such as wind and PV solar power are crucial for transitioning to carbon-free and sustainable energy systems, especially for agricultural and domestic applications in the desert and rural areas. However, implementing RE...
Deformation is one of the critical response quantities reflecting the structural safety of dams. To enhance outlier identification and denoising in dam deformation monitoring data, this study proposes a novel preprocessing method based on optimized V...
The present research develops the parametric estimation of a second-order transfer function in its standard form, employing metaheuristic algorithms. For the estimation, the step response with a known amplitude is used. The main contribution of this...
With the rapid development of a social economy, the yearly increase in air conditioning load in the winter and summer seasons may bring serious challenges to the safe and economic operation of the power grid during the peak period of electricity cons...
Cloud computing (CC) refers to an Internet-based computing technology in which shared resources, such as storage, software, information, and platform, are offered to users on demand. CC is a technology through which virtualized and dynamically scalab...
At present, the Beetle Antennae Search (BAS) algorithm has achieved remarkable success in image segmentation. However, when dealing with some complex image segmentation problems, particularly in the context of instance segmentation, which aims to ide...
Existing metaheuristic approaches often struggle to maintain an effective exploration–exploitation balance and are prone to premature convergence when addressing highly conflicting time–cost–safety–risk trade-off problems (TCS...
For radial distribution systems (RDSs) to operate efficiently, reliably, and sustainably, distributed generation (DG), capacitor banks (CBs), and network reconfiguration (NR) must be optimally allocated and sized. The main objectives considered in th...
Over the last decades, load forecasting is used by power companies to balance energy demand and supply. Among the several load forecasting methods, medium-term load forecasting is necessary for grid’s maintenance planning, settings of electrici...
The accelerated deployment of electric vehicles requires planning tools able to quantify how much charging infrastructure can be integrated into distribution systems without violating operational constraints. This paper proposes a multi-scenario opti...
This research evaluates the performance of six metaheuristic algorithms in the active and reactive power management of wind turbines (WTs) integrated into an AC microgrid (MG). The population-based genetic algorithm (PGA) is proposed as the primary o...
Multi-objective optimization has become an indispensable tool for solving engineering design and manufacturing problems involving multiple conflicting objectives. This paper presents a novel parameter-less multi-objective optimization (MOO) framework...
This paper presents an optimization-based scheduling strategy for battery energy storage systems (BESS) in alternating current microgrids, considering both grid-connected and islanded operation. The study addresses two independent objectives: minimiz...
The increasing integration of intermittent renewable energy sources (RESs) into islanded Hybrid Power Systems (HPSs) is a critical step towards global energy sustainability; however, it poses significant challenges to frequency stability owing to low...
The large-scale integration of photovoltaic generation into distribution grids has introduced significant operational challenges, including voltage excursions, reverse power flows, and increased variability. Battery energy storage systems (BESSs) off...
In this paper, a new modified particle swarm optimization, m-PSO, is proposed, in which the novelty consists of proposing a fitness-based particle swarm optimization algorithm, PSO, which adapts the particles’ behavior rather than the PSO param...