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  1. 1

    Evolutionary algorithms for VLSI multi-objective netlist partitioning by Sait, Sadiq M.

    Published 2006
    “…Further, we compared the results of the iterative heuristics with a modified FM algorithm, named PowerFM, which targets power optimization. …”
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    A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

    Published 2024
    “…<p dir="ltr">This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. …”
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    Reliability and fault tolerance based topological optimization of computer networks - part II: iterative techniques by Abd-El-Barr, Mostafa

    Published 2003
    “…We consider the use of three iterative techniques, namely tabu search, simulated annealing, and genetic algorithms, in solving the multiobjective topological optimization network design problem. …”
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    A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

    Published 2022
    “…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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    Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning by Sait, Sadiq M.

    Published 2006
    “…Further, we compared the results of the iterative heuristics with a modified FM algorithm, named PowerFM, which targets power optimization. …”
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    article
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    Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling by Majed Hadid (17148364)

    Published 2022
    “…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”
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    Fuzzy simulated evolution algorithm for VLSI cell placement by Sait, Sadiq M.

    Published 2003
    “…This approach can be followed by other iterative (meta-) heuristics to find desirable solutions to optimization problems with noisy search space and possibly more than one objective. …”
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    A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS by Youssef, H.

    Published 2020
    “…This choice is dictated by physical and technological constraints and must optimize several objectives. Important objectives are monetary cost, network delay, hop count between communicating pairs, and reliability. …”
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    Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

    Published 2024
    “…This work aims to enhance the performance of the K-means algorithm by introducing a novel method for selecting the initial centroids, thereby minimizing randomness and reducing the number of iterations needed to reach optimal results. …”
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    masterThesis
  15. 15

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

    Published 2020
    “…Abstract Evolutionary algorithms, simulated annealing (SA), and tabu search (TS) are general iterative algorithms for combinatorial optimization. …”
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    A new tabu search algorithm for the long-term hydro scheduling problem by Mantawy, A.H.

    Published 2002
    “…The proposed implementation contributes to the enhancement of speed and convergence of the original tabu search algorithm (TSA). A significant reduction in the objective function over previous classical optimization methods and a simulated annealing algorithm has been achieved. …”
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    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. …”
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    General iterative heuristics for VLSI multiobjective partitioning by Sait, Sadiq M.

    Published 2003
    “…In this paper, we engineer two iterative heuristics for the optimization of VLSI netlist bi-Partitioning. …”
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