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fly optimization » _ optimization (Expand Search), dog optimization (Expand Search), policy optimization (Expand Search)
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Teaching–learning-based optimization algorithm: analysis study and its application
Published 2024“…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …”
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Squirrel Search Algorithm for Portfolio Optimization
Published 2019“…However, the successes of nature-inspired algorithms in hard computational optimization problems have encouraged researchers to design and apply these algorithms for a variety of optimization problems. …”
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An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
Published 2022“…Therefore, it is imperative to account for these adverse effects of the integration of DERs on the distribution network and minimize their impact when calculating the Hosting Capacity (HC). Two algorithms are presented in this study derived from a novel modified iterative method and a novel Repeated Particle Swarm Optimization (RPSO) method for determining the HC for multiple DER units simultaneously or a single DER unit integrating into radial or mesh networks. …”
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A Scatter search algorithm for exam scheduling. (c2006)
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Developing a resilient framework for electric vehicle charging stations harnessing solar energy, standby batteries and grid integration with advanced control mechanisms
Published 2024“…Consequently, this article presents and evaluates a system that utilizes a proportional‐integral‐derivative controller, a neural network‐equipped grid and a charging station utilizing a Dragon Fly Optimization Algorithm to generate power and a maximum power point tracking controller. …”
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm
Published 2023“…This has been done using a new meta-heuristic algorithm, improved artificial rabbits optimization (IARO). …”
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Optimizing microgrid efficiency: Coordinating commercial and residential demand patterns with shared battery energy storage
Published 2024“…Utilizing a Firefly Algorithm (FA) for optimization, the study determines the optimized BESS capacity for minimum total cost. …”
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Optimizing transparent photovoltaic integration with battery energy storage systems in greenhouse: a daily light integral-constrained economic analysis considering BESS degradation
Published 2025“…Employing an enhanced Firefly Algorithm (FA) to optimize the PV cover ratio and BESS capacity, the analysis aims to maximize the Net Present Value (NPV) over a 25-year period, serving as the primary economic parameter. …”
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A Survey of Data Clustering Techniques
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Optimizing transparent photovoltaic integration with battery energy storage systems in greenhouse: a daily light integral-constrained economic analysis considering BESS degradation
Published 2025“…Employing an enhanced Firefly Algorithm (FA) to optimize the PV cover ratio and BESS capacity, the analysis aims to maximize the Net Present Value (NPV) over a 25-year period, serving as the primary economic parameter. …”
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Assessing the potential of network reconfiguration to improve distributed generation hosting capacity in active distribution systems
Published 2014“…The problem is formulated as a mixed-integer, nonlinear, multi-period optimal power flow (MP-OPF) which aims to maximize the DG hosting capacity under thermal and voltage constraints. …”
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Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Alg...
Published 2023“…The optimum capacity of EH equipment, including photovoltaic and wind renewable energy sources, a combined heat and power system (CHP), a boiler, energy storage, and electric vehicles is determined in the day-ahead market using the improved Fick’s law algorithm (IFLA), considering the energy profit maximization and also satisfying the linear network and hub constraints. …”
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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…This paper proposes a multilayer RDH method using the multilevel thresholding technique to reduce the difference value in pixels and increase the visual quality and the embedding capacity. Optimization algorithms are one of the most popular methods for solving NP-hard problems. …”
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DRL-Based IRS-Assisted Secure Visible Light Communications
Published 2022“…Our objective is to optimize the Secrecy Capacity (SC) by finding the optimal beamforming (BF) weights equipped at the VLC fixtures and mirror orientations at the mirror array sheet. …”
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An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems
Published 2024“…To assess the efficacy of the I-GKSO, it has been subjected to comparisons with multiple different algorithms. The trials conducted using FS datasets yield a quantitative consideration of the I-GKSO's capacity to attain the most optimal subset of features. …”
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A simulated annealing algorithm for the capacitated vehicle routing problem
Published 2017“…The Capacitated Vehicle Routing Problem (CVRP) is a combinatorial optimization problem where a fleet of delivery vehicles must service known customer demands from a common depot at a minimum transit cost without exceeding the capacity constraint of each vehicle. …”
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A simulated annealing algorithm for the capacitated vehicle routing problem
Published 2011“…The Capacitated Vehicle Routing Problem (CVRP) is a combinatorial optimization problem where a eet of delivery vehicles must service known customer demands from a common depot at a minimum transit cost without exceeding the capacity constraint of each vehicle. …”
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