An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems حسب Abdel-Salam, Mahmoud

"…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 حسب Azar, Danielle

"…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 حسب Azar, Danielle

"…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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Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems حسب Khaled Dhibi (16891524)

"…First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …"

An Optimal Energy Dispatch Management System for Hybrid Power Plants: PV-Grid-Battery-Diesel Generator-Pumped Hydro Storage حسب Fatma Ahmed (11084787)

A modified coronavirus herd immunity optimizer for capacitated vehicle routing problem حسب Abu Zitar, Raed

"…Capacitated Vehicle routing problem is NP-hard scheduling problem in which the main concern is to findthe best routes with minimum cost for a number of vehicles serving a number of scattered customersunder some vehicle capacity constraint. Due to the complex nature of the capacitated vehicle routingproblem, metaheuristic optimization algorithms are widely used for tackling this type of challenge.Coronavirus Herd Immunity Optimizer (CHIO) is a recent metaheuristic population-based algorithm thatmimics the COVID-19 herd immunity treatment strategy. …"
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm حسب Youssef, H.

"…Abstract The topology design of switched enterprise networks (SENs) is a hard constrained combinatorial optimization problem. The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …"
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm حسب Youssef, H.

"…Abstract The topology design of switched enterprise networks (SENs) is a hard constrained combinatorial optimization problem. The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …"
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A multi-objective planning approach for optimal DG allocation for droop based microgrids حسب Shaaban, Mostafa

"…The proposed formulation is compared to existing planning algorithms for droop-based microgrids. The re-sults show that including the secondary control region in the optimization problem achieves lower volt-age deviations and no frequency deviations at all demand levels. …"
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Optimal Routing and Scheduling in E-commerce Logistics using Crowdsourcing Strategies حسب Mohamed, Eman

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Multi-Agent Variational Approach for Robotics: A Bio-Inspired Perspective حسب Mir, Imran

"…This study proposes an adaptable, bio-inspired optimization algorithm for Multi-Agent Space Exploration. …"
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Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling حسب Majed Hadid (17148364)

"…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …"

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

"…Graph neural networks lower prediction error by up to thirty percent relative to descriptor-driven QSAR models for structurally diverse inhibitors. …"

Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace حسب Shahid, Saif Mohammad

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Enhancing e-learning through AI: advanced techniques for optimizing student performance حسب Rund Mahafdah (21399854)

"…AI algorithms, known for their cognitive ability and capacity to learn, adapt, and make decisions, are employed to analyze and forecast student performance, thereby improving educational quality and outcomes. …"

Particle swarm optimization approach for protein structure prediction in the 3D HP model حسب Mansour, Nashat

"…Our algorithm performs better than previous algorithms by finding lower energy structures or by performing fewer numbers of energy evaluations.…"
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Mobile Energy Storage Systems for Benefit Maximization in Resilient Smart Grids حسب Alshaal, Dima

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Energy conversion of heat from abandoned oil wells to mechanical refrigeration - Transient analysis and optimization حسب Mohammed Al-Khawaja (17093017)

"…Using the genetic algorithm optimization method with R1234ze(E) as working fluid in both power and cooling loops, a maximum power loop efficiency of 6.3% and COP of 5.3 were obtained at a high pressure of 29 bar (in the power loop) with minimal expander diameter of 64, compressor diameter of 171 mm, and 18 expander-compressor units.…"

Blood Glucose Regulation Modelling and Intelligent Control حسب Nasar, Nabeel

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On-site workshop investment problem: A novel mathematical approach and solution procedure حسب 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). …"