UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices by Samir, Moataz

“…Then, we develop an effective sub-optimal algorithm based on successive convex approximation in order to obtain results for larger network scenarios. …”
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Performance Assessment of Foraging Algorithms vs. Evolutionary Algorithms by El-Abd, Mohammed

“…This work provides a complete performance assessment of the four mentioned algorithms in comparison to the widely known differential evolution (DE), genetic algorithms (GAs), harmony search (HS), and particle swarm optimization (PSO) algorithms when applied to the problem of unconstrained nonlinear continuous function optimization. …”
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Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests by Kenneth V. Price (17877002)

“…Simulations demonstrate that “U-scores” are much more effective than dominance when tasked with identifying the better of two algorithms. We validate U-scores by having them determine the winners of the CEC 2022 competition on single objective, bound-constrained numerical optimization.…”

Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting by AlSayegh, Hadeel Yacoub

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An evolutionary algorithm for network topology design by Youssef, H.

“…The topology design of campus networks is a hard constrained combinatorial optimization problem, dictated by physical and technological constraints and must optimize several objectives. …”
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Artificial neural network algorithms. (c1999) by Ramadan, Samer N.

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Implementation of trust region methods in optimization. (c1998) by Hajj, Mohammed Omar

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Optimal shunt compensators at nonsinusoidal busbars by El-Amin, I.M.

“…The Direct Search Polytope algorithm is used. The solution of this model yields an optimal shunt LC compensator for the nonlinear load. …”
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Tabu search based circuit optimization by Sait, Sadiq M.

“…In this paper we address the problem of optimizing mixed CMOS/BiCMOS circuits. The problem is formulated as a constrained combinatorial optimization problem and solved using an tabu search algorithm. …”
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Fuzzy simulated evolution algorithm for topology design of campusnetworks by Youssef, H.

“…The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes) and links. …”
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Environmental/economic power dispatch using multiobjective evolutionary algorithms by Abido, M.A.

“…The EED problem is formulated as a nonlinear constrained multiobjective optimization problem. A new strength Pareto evolutionary algorithm (SPEA) based approach is proposed to handle the EED as a true multiobjective optimization problem with competing and noncommensurable objectives. …”
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A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS by Youssef, H.

“…ABSTRACT The topology design of campus networks is a hard constrained combinatorial optimization problem. It consists of deciding the number, type, and location of the active network elements (nodes), and the links. …”
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OPTIMAL SHUNT COMPENSATORS AT NON-SINUSOIDAL BUSBARS by El-Amin, I.M.

“…The Direct Search Polytope algorithm is used. The solution of this model yields an optimal shunt LC compensator for the nonlinear lend. …”
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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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An analytical framework for high-speed hardware particle swarm optimization by El-Abd, Mohammed

“…Engineering optimization techniques are computationally intensive and can challenge implementations on tightly-constrained embedded systems. …”
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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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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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