Final exams scheduling for univeristies. (c2001) by Timany, Mazen Nuhad

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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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Low-Cost Reduced Navigation System for Mobile Robot in Indoor/Outdoor Environments by Al Khatib, Ehab

“…EKF indoor localization is based on landmarks extracted from the depth measurements. …”
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Definition and selection of fuzzy sets in genetic‐fuzzy systems using the concept of fuzzimetric arcs by Kouatli, Issam

“…Design/methodology/approach – The design was based on two principles: selection and optimization. …”
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Multi-UAV-Enabled Mobile Edge Computing IoT Systems: Joint Association and Resource Allocation Framework by Abu Farha, Yazan Mahmoud

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Data Generation for Path Testing by Mansour, Nashat

“…These algorithms are based on an optimization formulation of the path testing problem which include both integer- and real-value test cases. …”
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Protein structure prediction in the 3D HP model by Abu-Khzam, Faisal

“…In this paper, we present a Particle Swarm Optimization (PSO) based algorithm for predicting protein structures in the 3D HP model. …”
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The bus sightseeing problem by Qian Hu (205735)

“…A mixed-integer programming formulation for the BSP is provided and solved by a Benders decomposition algorithm. For large-scale instances, an iterated local search based metaheuristic algorithm is developed with some tailored neighborhood operators. …”

FAST FUZZY FORCE-DIRECTED/SIMULATED EVOLUTION METAHEURISTIC FOR MULTIOBJECTIVE VLSI CELL PLACEMENT by Sait, Sadiq M.

“…SE is hybridized with force directed algorithm to speed-up the search. The proposed schemes are compared with previously presented SE based heuristics. …”
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Second-order conic programming for data envelopment analysis models by Mourad, Nahia

“…Indeed, the aforesaid method is based on mathematical optimization. This paper constructs a second-order conic optimization problem unifying several DEA models. …”
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Automated quantification of penile curvature using artificial intelligence by Tariq O. Abbas (11247771)

“…<h3>Objective</h3><p dir="ltr">To develop and validate an artificial intelligence (AI)-based algorithm for capturing automated measurements of Penile curvature (PC) based on 2-dimensional images.…”

Morphology for Planar Hexagonal Modular Self-Reconfigurable Robotic Systems by Sadjadi, Hossein

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Genetic Fuzzimetric Technique (GFT) by Kouatli, Issam

“…Integration of fuzzy systems with genetic algorithm has been identified by researchers as a useful technique of optimizing systems under uncertainty. …”
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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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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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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function by Boukas, EK

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Finite state machine state assignment for area and power minimization by El-Maleh, A.

“…A fuzzy-based aggregation function is employed to combine the two objectives. …”
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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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Enhancement of Frequency Control for Stand-Alone Multi-Microgrids by Kavita Singh (182141)

“…For getting superior outcomes and enhanced steadiness of the microgrid, the controller gains are streamlined utilizing an imperialist competitive algorithm (ICA). To demonstrate the efficiency of ICA, The obtained results are compared with the genetic algorithm and particle swarm optimization algorithm. …”