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Showing 1 - 12 results of 12 for search '(( slower optimization algorithm ) OR ( unconstrained optimization algorithm ))', query time: 0.09s Refine Results
  1. 1
    A new family of multi-step quasi-Newton algorithms for unconstrained optimization

    A new family of multi-step quasi-Newton algorithms for unconstrained optimization by Obeid, Samir

    Published 1999
    “…It concentrates on deriving a variable-metric family of minimum curvature algorithms for unconstrained optimization. The derivation is based on considering a rational model, with a certain tuning parameter, where the aim is to develop a general framework that encompasses all possible two-step minimum curvature algorithms generated by appropriate parameter choices. …”
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  2. 2
    Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems

    Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems by Agushaka, Jeffrey O.

    Published 2022
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  3. 3
    A family of minimum curvature variable-methods for unconstrained optimization. (c1998)

    A family of minimum curvature variable-methods for unconstrained optimization. (c1998) by Obeid, Samir Y.

    Published 1998
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  4. 4
    A new minimum curvator multi-step method for unconstrained optimization

    A new minimum curvator multi-step method for unconstrained optimization by Obeid, Samir

    Published 1998
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  5. 5
    Squirrel Search Algorithm for Portfolio Optimization

    Squirrel Search Algorithm for Portfolio Optimization by Dhaini, Mahdi

    Published 2019
    “…In this paper, we design and adapt a Squirrel Search Algorithm (SSA) for the unconstrained and constrained portfolio optimization problems. …”
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  6. 6
    Physical optimization algorithms for mapping data to distributed-memory multiprocessors

    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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  7. 7
    Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations

    Allocating data to multicomputer nodes by physical optimization algorithms for loosely synchronous computations by Mansour, Nashat

    Published 1992
    “…For example, the annealing and genetic algorithms produce better solutions and do not show a bias towards particular problem structures, but they are slower than the neural network algorithms. …”
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  8. 8
    Performance Assessment of Foraging Algorithms vs. Evolutionary Algorithms

    Performance Assessment of Foraging Algorithms vs. Evolutionary Algorithms by El-Abd, Mohammed

    Published 2012
    “…This work provides a complete performance assessment of the four mentioned algorithms in comparison to the widely known differential evolution (DE), genetic algorithms (GAs), harmony search (HS), and particle swarm optimization (PSO) algorithms when applied to the problem of unconstrained nonlinear continuous function optimization. …”
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  9. 9
    Implementation of trust region methods in optimization. (c1998)

    Implementation of trust region methods in optimization. (c1998) by Hajj, Mohammed Omar

    Published 1998
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  10. 10
    Loss Model Control for Efficiency Optimization and Advanced Sliding Mode Controllers with Chattering Attenuation for Five-Phase Induction Motor Drive

    Loss Model Control for Efficiency Optimization and Advanced Sliding Mode Controllers with Chattering Attenuation for Five-Phase Induction Motor Drive by Hassen Moussa (19759911)

    Published 2024
    “…<p dir="ltr">This paper proposes firstly a Second Order Sliding Mode Control (SOSMC) based on a Super Twisting Algorithm (STA) (SOSMC-STA) combined with a Direct Field-Oriented Control (DFOC) strategy of a Five-Phase Induction Motor (FPIM). …”
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  11. 11
    Iterative Least Squares Functional Networks Classifier

    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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  12. 12
    Design and analysis of entropy-constrained reflected residual vector quantization

    Design and analysis of entropy-constrained reflected residual vector quantization by Mousa, W.A.H.

    Published 2002
    “…Residual vector quantization (RVQ) is a vector quantization (VQ) paradigm which imposes structural constraints on the encoder in order to reduce the encoding search burden and memory storage requirements of an unconstrained VQ. Jointly optimized RVQ (JORVQ) is an effective design algorithm for minimizing the overall quantization error. …”
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