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  1. 41

    Simulated Annealing and Genetic Algorithms for Optimal Regression Testing by Mansour, Nashat

    Published 1999
    “…We present two natural optimization algorithms, namely, a simulated annealing and a genetic algorithm, for solving this problem. …”
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    article
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    Indoor Localization Based on Floor Plans and Power Maps by Khalifeh, Joe J.

    Published 2015
    “…An indoor localization algorithm that is based on fingerprinting and trilateration is developed. …”
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    conferenceObject
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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)

    Published 2023
    “…<p>Non-parametric tests can determine the better of two stochastic optimization algorithms when benchmarking results are ordinal—like the final fitness values of multiple trials—but for many benchmarks, a trial can also terminate once it reaches a prespecified target value. …”
  7. 47

    A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

    Published 2024
    “…The ES algorithm begins with a random initial solution and uses an insertion mutation to optimize the solution. …”
  8. 48

    Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

    Published 2022
    “…Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
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  9. 49

    Parallel physical optimization algorithms for allocating data to multicomputer nodes by Mansour, Nashat

    Published 1994
    “…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …”
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  10. 50

    A Survey of cuckoo search algorithm: optimizer and new applications by Abualigah, Laith

    Published 2024
    “…Cuckoo search (CS) is an efficient swarm intelligence-based algorithm that has come a long way since its start in 2009. …”
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  11. 51

    Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

    Published 2004
    “…This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …”
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    masterThesis
  12. 52

    Physical optimization algorithms for mapping data to distributed-memory multiprocessors by Mansour, Nashat

    Published 1992
    “…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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    masterThesis
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    Optimal selection of the forgetting matrix into an iterative learning control algorithm by Saab, Samer S.

    Published 2005
    “…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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  15. 55

    Optimal VAR Dispatch Using a Multiobjective Evolutionary Algorithm by Abido, M. A.

    Published 2005
    “…A new Strength Pareto Evolutionary Algorithm based approach is proposed to handle the problem as a true multiobjective optimization problem with competing and non-commensurable objectives. …”
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    article
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    MSLP: mRNA subcellular localization predictor based on machine learning techniques by Saleh Musleh (15279190)

    Published 2023
    “…We propose a novel combination of four types of features representing k-mer, pseudo k-tuple nucleotide composition (PseKNC), physicochemical properties of nucleotides, and 3D representation of sequences based on Z-curve transformation to feed into machine learning algorithm to predict the subcellular localization of mRNAs.…”
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    Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

    Published 2018
    “…We formulate the testing problem as an optimization problem and use a simulated annealing (SA) metaheuristic algorithm to generate test cases as sequences of events while keeping the test suite size reasonable. …”
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