A multi-objective planning approach for optimal DG allocation for droop based microgrids by Shaaban, Mostafa

“…This paper proposes a multi-objective planning approach to determine the optimal DG locations for droop-based microgrids. A secondary control operating region is mathematically formulated and incor-porated in the multi-objective optimization problem to constrain the optimal droop characteristic within the acceptable frequency and voltage thresholds. …”
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Optimal location and sizing of renewable distributed generations and electric vehicle charging stations by Guindi, Marina

“…The study introduces several constraints, including the placement of EVCSs and RDGs at separate buses, and employs particle swarm optimization and cuckoo search algorithm to simultaneously determine the optimal locations and sizes of the RDGs and the optimal locations of the EVCSs. …”
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An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks by Md Moktadir Rahman (16904751)

“…An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed for the load controller to provide fast convergence and robust optimization results. …”

Defense against adversarial attacks: robust and efficient compressed optimized neural networks by Insaf Kraidia (19198012)

“…First, introducing a pioneering batch-cumulative approach, the exponential particle swarm optimization (ExPSO) algorithm was developed for meticulous parameter fine-tuning within each batch. …”

Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment by Farhat Mahmood (15468854)

“…A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …”

Shape and sizing optimisation of space truss structures using a new cooperative coevolutionary-based algorithm by Dehkordi, Amin Abdollahi

“…This novel alternative optimisation strategy (CCMPA-GS) compared with 13 established genetic, evolutionary, swarm, and memetic meta-heuristic optimisation algorithms. …”
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A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability by Debabrata Mazumdar (18560506)

“…Performance of HA's is compared with three established optimization algorithms: Grey Wolf Optimization, Cuckoo Search Algorithm and Particle‐Swarm Optimization across different operating scenarios and partial shading circumstances. …”

Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm by Odat, Alhaj-Saleh A.

“…The model aims to compare the performance of classical perturb and observe (P&O) algorithm, particle swarm optimization (PSO) algorithm, flower pollination algorithm (FPA), and SMC-based tracking techniques. …”
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An Energy Efficient Wireless Sensor Network for Optimal Routing using Hybridized Bio-Inspired Technique by Askarovich, Ulashev Hubbim

“…While clustering techniques, such as Low Energy Adaptive Clustering Hierarchy (LEACH), help reduce energy usage, they suffer from inefficient local searches and poor exploration-exploitation balance.To address these limitations, this study proposes a hybrid bio-inspired optimization technique—Modified Harmony Search Algorithm (MHSA) combined with Competitive Swarm Optimization (CSO)—for optimal cluster head (CH) selection. …”
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A Novel Link-based Multi-objective Grey Wolf Optimizer for Appliances Energy Scheduling Problem by Abou Doush, Iyad

“…For comparative purposes, the same linked-based neighbourhood selection strategy is utilized with other three optimization algorithms, including particle swarm optimization, salp swarm optimization, and wind-driven algorithm. …”
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Thermodynamic Analysis and Optimization of Densely-Packed Receiver Assembly Components in High-Concentration CPVT Solar Collectors by Sharaf, Omar Z.

“…Finally, using the developed design models and simulation algorithms, constrained non-linear multi-variable geometric optimization of the assembly components has been carried out to obtain minimum pumping power, maximum extractor heat transfer coefficient, and maximum thermoelectric power output. …”
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Enhancing multilayer perceptron neural network using archive-based harris hawks optimizer to predict gold prices by Abu Doush, Iyad

“…The performance of the proposed AHHO-NN model is compared against four swarm intelligence algorithms (i.e., HHO-NN, JAYA-NN, MFO-NN, PSO-NN) as well as four classical machine learning techniques (i.e., linear regression (LR), MLP Regressor (MLP), RANSAC Regressor (RANSAC), and TheilSen Regressor (TR)). …”
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Improving multilayer perceptron neural network using two enhanced moth-flame optimizers to forecast iron ore prices by Ahmed, Basem

“…We compare our two proposed MFO algorithms, the roulette wheel moth-flame optimization algorithm and the global best moth-flame optimization algorithm, against four swarm intelligence algorithms and five classical machine learning techniques when predicting the iron ore price. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

“…To solve the proposed model, four meta-heuristic algorithms, namely multi-objective particle swarm optimization (MOPSO), a non-dominated sorting genetic algorithm (NSGA-II), a hybrid of k-medoids as a famous clustering algorithm and NSGA-II (KNSGA-II), and a hybrid of K-medoids and MOPSO (KMOPSO) are implemented. …”

Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …”

An optimization approach to increasing sustainability and enhancing resilience against environmental constraints in LNG supply chains: A Qatar case study by Sara Al-Haidous (18095368)

“…The developed model, which is implemented using the Binary Particle Swarm Optimization algorithm subjected to economic and environmental objectives within an overarching strategic aim for sustainability and resilience. …”

On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

“…Computational experiments show that the proposed method has solved most of the instances of the addressed problem to optimality and outperformed the existing metaheuristics, e.g., Simulated Annealing (SA) and Particle Swarm Optimization (PSO). …”

A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System by Ekinci, Serdar

“…CEC2019 test suite is also used to perform ablation experiments to reveal the separate contributions of chaotic local search and modified opposition-based learning strategies to the CmOBL-AO algorithm. For the vehicle cruise control system, we confirm the more excellent performance of the proposed method against particle swarm, gray wolf, salp swarm, and original Aquila optimizers using statistical, Wilcoxon signed-rank, time response, robustness, and disturbance rejection analyses. …”
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Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP by Abdelhafez, Nada

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Enhanced Control of Single-Stage PV-STATCOM Using Hybrid MPPT and Adaptive AHLMS for Power Quality Improvement by Nagwa F. Ibrahim (17334201)

“…It employs a hybrid pelican and perturbs and observe and particle swarm optimization (PSO) based maximum power point tracking (MPPT) algorithm to consistently extract peak power from the PV array. …”