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  1. 421
    GENETIC SCHEDULING OF TASK GRAPHS

    GENETIC SCHEDULING OF TASK GRAPHS by Benten, M. S.

    Published 2020
    “…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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  2. 422
    A LINEAR-PROGRAMMING APPROACH FOR THE WEIGHTED GRAPH MATCHING PROBLEM

    A LINEAR-PROGRAMMING APPROACH FOR THE WEIGHTED GRAPH MATCHING PROBLEM by Al-Mohamad, HA

    Published 2020
    “…A linear program is obtained by formulating the graph matching problem in L1 norm and then transforming the resulting quadratic optimization problem to a linear one. The linear program is solved using a Simplex-based algorithm. …”
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  3. 423
    Final exams scheduling for univeristies. (c2001)

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

    Published 2001
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  4. 424
    Power system output feedback stabilizer design via geneticalgorithms

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

    Published 1997
    “…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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  5. 425
    Definition and selection of fuzzy sets in genetic‐fuzzy systems using the concept of fuzzimetric arcs

    Definition and selection of fuzzy sets in genetic‐fuzzy systems using the concept of fuzzimetric arcs by Kouatli, Issam

    Published 2008
    “…Design/methodology/approach – The design was based on two principles: selection and optimization. …”
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  6. 426
    Data Generation for Path Testing

    Data Generation for Path Testing by Mansour, Nashat

    Published 2004
    “…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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  7. 427
    Protein structure prediction in the 3D HP model

    Protein structure prediction in the 3D HP model by Abu-Khzam, Faisal

    Published 2009
    “…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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  8. 428
    FAST FUZZY FORCE-DIRECTED/SIMULATED EVOLUTION METAHEURISTIC FOR MULTIOBJECTIVE VLSI CELL PLACEMENT

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

    Published 2006
    “…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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  9. 429
    2022 IEEE Congress on Evolutionary Computation (CEC)

    2022 IEEE Congress on Evolutionary Computation (CEC) by El-Abd, Mohammed

    Published 2022
    “…RL is used to select the best-performing action among three of them in the optimization process to evolve a set of solution based on the population state and reward value. …”
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  10. 430
    Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management

    Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management by Islam, Eljilany

    Published 2022
    “…The benefit of the interventional algorithm was based on estimated reduction in the probabilities of clinical events and their cost, added to the avoided cost because of canceled procedures. …”
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  11. 431
    Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management

    Cost-Benefit Analysis of Genotype-Guided Interruption Days in Warfarin Pre-Procedural Management by Islam Eljilany (14151588)

    Published 2023
    “…The benefit of the interventional algorithm was based on estimated reduction in the probabilities of clinical events and their cost, added to the avoided cost because of canceled procedures. …”
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  12. 432
    Second-order conic programming for data envelopment analysis models

    Second-order conic programming for data envelopment analysis models by Mourad, Nahia

    Published 2022
    “…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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  13. 433
    Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves

    Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves by S. Andhale, Yogesh

    Published 2018
    “…The genetic optimization (GO) method is used to further refine the location of damage within the enclosed area obtained using astroid algorithm. …”
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  14. 434
    Morphology for Planar Hexagonal Modular Self-Reconfigurable Robotic Systems

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

    Published 2009
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  15. 435
    Genetic Fuzzimetric Technique (GFT)

    Genetic Fuzzimetric Technique (GFT) by Kouatli, Issam

    Published 2012
    “…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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  16. 436
    UAV Trajectory Planning for Data Collection from Time-Constrained IoT Devices

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

    Published 2019
    “…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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  17. 437
    Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function

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

    Published 2020
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  18. 438
    Finite state machine state assignment for area and power minimization

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

    Published 2006
    “…A fuzzy-based aggregation function is employed to combine the two objectives. …”
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  19. 439
    Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function

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

    Published 2020
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  20. 440
    Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function

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

    Published 2020
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