A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems by Kandil, Sarah M.

“…The formulation employs a general objective function that optimizes the total Annual Cost of Energy (ACOE). …”
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Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach by Haitham Osman (11737057)

“…<p>This paper presents the design, modeling, and multi-objective optimization of an advanced solar energy system based on concentrated solar power technology, aimed at sustainable electricity generation in urban environments. …”

A Literature Review on System Dynamics Modeling for Sustainable Management of Water Supply and Demand by Khawar Naeem (17984062)

“…The models included agent-based modeling (ABM), Bayesian networking (BN), analytical hierarchy approach (AHP), and simulation optimization multi-objective optimization (MOO). The solution approaches included the genetic algorithm (GA), particle swarm optimization (PSO), and the non-dominated sorting genetic algorithm (NSGA-II). …”

Software defect prediction. (c2019) by Moussa, Rebecca

“…One that focuses on predicting defect in software modules using a hybrid heuristic - a combination of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). We compare our approach to 9 well known machine learning techniques and results show the advantages of our model over the other techniques. …”
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DRL-Based IRS-Assisted Secure Visible Light Communications by Danya A. Saifaldeen (19498705)

“…The DDPG-based algorithm provides an optimized solution that can adapt to the large size of design parameters and act fast to the channel variations due to users’ mobility. …”

Reinforcement Learning for Resilient Aerial-IRS Assisted Wireless Communications Networks in the Presence of Multiple Jammers by Zain Ul Abideen Tariq (17984107)

“…Hence, we leverage the light-weight Deep Reinforcement Learning (DRL) technique called Deep Deterministic Policy Gradient (DDPG) to optimize trajectory and IRS phase shifts and achieve multiple objectives jointly. …”

The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

Meta Reinforcement Learning for UAV-Assisted Energy Harvesting IoT Devices in Disaster-Affected Areas by Marwan Dhuheir (19170898)

“…We conducted extensive simulations and compared our approach with two state-of-the-art models using traditional RL algorithms represented by a deep Q-network algorithm, a Particle Swarm Optimization (PSO) algorithm, and one greedy solution. …”

Secrecy Performance of Decode-and-Forward Based Hybrid RF/VLC Relaying Systems by Jaber Al-Khori (16855470)

Power system output feedback stabilizer design via geneticalgorithms by Abdel-Magid, Y.L.

“…A digital simulation of the power system is then used in conjunction with the genetic algorithm to determine the output feedback gains. In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. …”
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GENETIC SCHEDULING OF TASK GRAPHS by Benten, M. S.

“…The problem of assigning tasks to processing elements as a combinatorital optimization is formulated, and a heuristic based on a genetic algorithm is presented. …”
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Simulated evolution for timing and low power VLSI standard cell placement by Sait, Sadiq M.

“…Abstract This paper presents a Fuzzy Simulated Evolution algorithm for VLSI standard cell placement with the objective of minimizing power, delay and area. …”
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An innovative simulated annealing approach to the long-term hydroscheduling problem by Mantawy, A.H.

“…A significant reduction in the number of the objective function evaluations, and consequently less iterations are required to reach the optimal solution. …”
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"A Tabu Search Approach for the Design of Variable Structure Load Frequency Controller Incorporating Model Nonlinearities" by Al-Hamouz, Z.

“…The proposed method formulates the design of VSC as an optimization problem and utilizes Tabu Search Algorithm (TS) to find the optimal settings of the controller. …”
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FAST FUZZY FORCE-DIRECTED/SIMULATED EVOLUTION METAHEURISTIC FOR MULTIOBJECTIVE VLSI CELL PLACEMENT by Sait, Sadiq M.

“…In this paper, a novel technique is presented to address this hard problem, while optimizing multiple objectives. A major difculty with such multi-objective combinatorial optimization problems is the existence of a very large solution search space, one of which is the desired optimal solution. …”
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Robust tuning of power system stabilizers in multimachine powersystems by Abdel-Magid, Y.L.

“…The problem of selecting the stabilizer parameters is converted to a simple optimization problem with an eigenvalue-based objective function, which is solved by a tabu search algorithm. …”
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Finite state machine state assignment for area and power minimization by El-Maleh, A.

“…In this paper, we address the problem of FSM state assignment to minimize area and power. The objectives are targeted as single/independent as well as multi-objective optimization (MOP) problems. …”
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Impacts of On-Grid Solar PV on Distribution Networks and Potential Solutions: A Case Study in the Region of Zahle by Korkmaz, Jessica

“…The siting and sizing methodology is conducted by considering five different optimization algorithms, namely the single-objective genetic algorithm (SOGA), the combined SOGA and loss sensitivity factor algorithm (SOGA-LSF), the multi-objective genetic algorithm (MOGA), the combined MOGA-LSF and the CAPADD algorithm of OpenDSS. …”
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Complexity Avoidance using Biological Resemblance of Modular Multivariable Structure by Kouatli, Issam

“…GFT (Genetic Fuzzimetric Technique) is of no exception which merges Fuzzy logic with genetic algorithm to achieve the optimization of the decision making process under uncertainty. …”
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A utility minimization approach for energy-aware cooperative content distribution with fairness constraints by Yaacoub, Elias

“…Thus, to ensure fairness in energy consumption, a low complexity utility minimization algorithm is proposed. Using the appropriate utilities, the algorithm can be used to implement the optimal greedy energy minimization solution or to ensure different degrees of fairness in energy consumption. …”
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