Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

“…Abstract Evolutionary algorithms, simulated annealing (SA), and tabu search (TS) are general iterative algorithms for combinatorial optimization. …”
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A new multiobjective evolutionary algorithm forenvironmental/economic power dispatch by Abido, A.A.

“…In this paper, a new multiobjective evolutionary algorithm for environmental/economic power dispatch (EED) optimization problem is presented. …”
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A modified ant colony algorithm for evolutionary design of digital circuits by Sait, Sadiq M.

“…In this paper, a multiobjective optimization of logic circuits based on a modified ant colony (ACO) algorithm is presented. …”
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CFD Based Airfoil Shape Optimization for Aerodynamic Drag Reduction by Khot, Mohammed Taha Shafiq

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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm by 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 by 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 Review on Swarm Intelligence and Evolutionary Algorithms for Solving the Traffic Signal Control Problem by Shaikh, Palwasha

“…Nature-inspired algorithms including evolutionary and swarm intelligence algorithms are gaining a lot of momentum. …”
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Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem by Haraty, Ramzi A.

“…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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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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Nonlinear clustering optimization for scalable data mining in cloud and quantum computing environments by Manjula, S.

“…The article outlines an optimization model of nonlinear clustering that could strike a balance between the use of the complex mathematical models and scalability to the cloud and quantum computing systems. …”
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Hybrid quantum–cloud framework for nonlinear clustering optimization and intelligent resource management by Abdullayev, Ilyos

“…These weaknesses will be mitigated by the proposed framework that will integrate quantum-inspired algorithms (which will operate on variational quantum circuits and Quantum Approximate Optimization Algorithm (QAOA)) with cloud-native orchestration solutions, only that reinforcement learning-based scheduling will be integrated. …”
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Small-Signal Stability Analysis and Parameters Optimization of Virtual Synchronous Generator for Low-Inertia Power System by Alaa Altawallbeh (22565837)

“…We further propose a hybrid Particle Swarm Optimization (PSO) algorithm with a multi-objective cost function to optimize VSG controller gains. …”

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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The survey of cluster based data collection process for iot enabled wireless sensor network using several optimization technique by Abirami, R.

“…The study analyses nature-based metaheuristic methods such as the Genetic Algorithms, Particle Swarm Optimization, Firefly Optimization, Gray Wolf Optimization and Water-Cycle Algorithms, and specialised protocols of clustering, routing and data aggregation. …”
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An Enhanced Binary Rat Swarm Optimizer based on Local-best Concepts of PSO and Collaborative Crossover Operators for Feature Selection by Abou Doush, Iyad

“…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”
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Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP by Abdelhafez, Nada

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Evacuation of a highly congested urban city by El Khoury, John

“…In this paper, we present a capacity-constrained routing optimization approach to maximize the total evacuees for short notice evacuation planning in case of both natural and/or man-made disasters. …”
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2022 IEEE Congress on Evolutionary Computation (CEC) by El-Abd, Mohammed

“…We tested the performance of the proposed IMODEII by considering 12 benchmark functions with 10 and 20 variables taken from CEC2022 competition on single objective bound constrained numerical optimisation. A comparison between the proposed IMODEII and the state-of-the-art algorithms is conducted, with the results demonstrating the efficiency of the proposed IMODEII.…”
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Morphology for Planar Hexagonal Modular Self-Reconfigurable Robotic Systems by Sadjadi, Hossein

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Peak Loads Shaving in a Team of Cooperating Smart Buildings Powered Solar PV-Based Microgrids by Ahmed Ouammi (14151039)

“…The main objective is to formulate a constrained optimization problem embedded in a model predictive control (MPC) scheme to optimally control the operation of each microgrid to reduce/shave the peak load in case of occurrence, optimizing the power flows exchanges and energy storages, while ensuring a high quality of service to the EVs owners in each microgrid. …”