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  1. 481

    Dynamic single node failure recovery in distributed storage systems by Itani, M.

    Published 2017
    “…The contributions of the paper are four fold: (i) generating an optimized block distribution scheme among the nodes of a given data center for fixed and variable size blocks; (ii) optimization of storage allocation under dynamic environments with data block arrivals; (iii) optimization of storage allocation with newly added storage nodes; and (iv) generating an effective block distribution scheme among the nodes by accounting for varying priorities among data blocks. …”
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  2. 482

    A METHODOLOGY FOR NETWORK TOPOLOGY DESIGN USING FUZZY EVALUATIONS by Khan, Salman A.

    Published 2020
    “…This methodology is based on two algorithms, namely, fuzzy simulated evolution algorithm and the augmenting path algorithm. …”
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    article
  3. 483
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  6. 486

    Tuning of AGC of interconnected reheat thermal systems with geneticalgorithms by Abdel-Magid, Y.L.

    Published 1995
    “…This paper deals with the application of genetic algorithms for optimizing the automatic generation control (AGC) systems. …”
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    article
  7. 487

    Traffic Offloading with Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks by Abbas, Nadine

    Published 2018
    “…We also propose efficient sub-optimal hierarchical tree-based algorithms that operate in real time with dynamic and fast solutions for ultra dense networks. …”
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    article
  8. 488

    An evolutionary meta-heuristic for state justification insequential automatic test pattern generation by El-Maleh, A.H.

    Published 2001
    “…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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    article
  9. 489

    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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    article
  10. 490
  11. 491

    A combinatorial auction‐based approach for ridesharing in a student transportation system by Chefi Triki (14158860)

    Published 2023
    “…Three meta-heuristics, namely particle swarm optimization, dragonfly algorithm, and imperialist competitive algorithm, are implemented in the proposed framework, whose performances are assessed and compared. …”
  12. 492

    Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks by Kalash, Saeddin

    Published 2025
    “…In the second, we consider optimized UAV position adaptation where we generated the problem as a multi-objective optimization problem and solved it as a mixed-integer linear programming problem with constraints related to UAV range, UAV steps, and time constraints. …”
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    masterThesis
  13. 493

    The Generalization of Bidirectional Dual Active Bridge DC/DC Converter Modulation Schemes: State-of-the-Art Analysis under Triple Phase Shift Control by Yasen Harrye (22415632)

    Published 2023
    “…Additionally, a generic optimization algorithm is developed to show the advantages of TPS modulation, and thus, the analysis in this paper offers a valuable insight for single-phase DAB converter designers in identifying a wide range of optimization algorithms to achieve higher efficiency under TPS modulation. …”
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  16. 496

    EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING by Sait, Sadiq M.

    Published 2020
    “…The interest in finding an optimal partitioning especially in VLSI, and has been a hot issue in recent years. …”
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    article
  17. 497

    A linear programming approach for the weighted graph matchingproblem by Almohamad, H.A.

    Published 1993
    “…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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  18. 498

    Iterative heuristics for multiobjective VLSI standard cellplacement by Sait, Sadiq M.

    Published 2001
    “…We employ two iterative heuristics for the optimization of VLSI standard cell placement. These heuristics are based on genetic algorithms (GA) and tabu search (TS) respectively. …”
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    article
  19. 499

    Simulated evolution for timing and low power VLSI standard cell placement by Sait, Sadiq M.

    Published 2020
    “…For this hard multiobjective combinatorial optimization problem, no known exact and efficient algorithms exist that guarantee finding a solution of specific or desirable quality. …”
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    article
  20. 500

    Iterative Least Squares Functional Networks Classifier by Faisal, Kanaan A

    Published 2007
    “…Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. …”
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