Showing 41 - 60 results of 350 for search '(((( algorithm a function ) OR ( algorithm 1 function ))) OR ( algorithms within function ))', query time: 0.22s Refine Results
  1. 41
  2. 42

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

    Published 2020
    “…The three heuristics are applied on the same optimization problem and compared with respect to (1) quality of the best solution identified by each heuristic, (2) progress of the search frominitial solution(s) until stopping criteria are met, (3) the progress of the cost of the best solution as a function of time (iteration count), and (4) the number of solutions found at successive intervals of the cost function. …”
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  3. 43

    Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm by Zerguine, A.

    Published 2000
    “…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
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  4. 44

    A parallel tabu search algorithm for VLSI standard-cell placement by Suit, S.M.

    Published 2000
    “…In this work, tabu search placement algorithm is parallelized on a network of workstations using PVM. …”
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    article
  5. 45

    A comparative study of ElGamal based digital signature algorithms by Haraty, Ramzi A.

    Published 2006
    “…To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
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    article
  6. 46

    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. …”
  7. 47

    Scatter Search algorithm for Protein Structure Prediction by Mansour, Nashat

    Published 2016
    “…Given the protein's sequence of Amino Acids (AAs), our algorithm produces a 3D structure that aims to minimise the energy function associated with the structure. …”
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  8. 48

    An improved kernelization algorithm for r-Set Packing by Abu-Khzam, Faisal N.

    Published 2010
    “…Our result improves on previously known kernelizations by a factor of k. In particular, the number of elements in a 3-Set Packing kernel is improved from a cubic function of the parameter to a quadratic one.…”
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  9. 49

    Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

    Published 1999
    “…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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  10. 50

    LINE SEARCH TECHNIQUES FOR THE LOGARITHMIC BARRIER FUNCTION IN QUADRATIC-PROGRAMMING by Bendaya, M.

    Published 2020
    “…In this paper, we propose a line-search procedure for the logarithmic barrier function in the context of an interior point algorithm for convex quadratic programming. …”
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  11. 51

    GAP - A GENETIC ALGORITHM APPROACH TO OPTIMIZE 2-BIT DECODER PLAS by Benten, M. S.

    Published 2020
    “…This paper describes a minimization procedure that uses a genetic algorithm approach to reduce the size to the two bit decoder PLAs. …”
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    article
  12. 52

    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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  13. 53

    A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem by Mantawy, A. H.

    Published 2020
    “…This paper presents a new algorithm based on integrating the use of genetic algorithms and tabu search methods to solve the unit commitment problem. …”
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    article
  14. 54

    Thyristor controlled phase shifter based stabilizer design usingsimulated annealing algorithm by Abido, M.A.

    Published 1999
    “…This paper presents a thyristor controlled phase shifter (TCPS) based stabilizer design using the simulated annealing (SA) algorithm. …”
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  15. 55

    Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem by Montawy, A.H.

    Published 2020
    “…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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    article
  16. 56

    Simultaneous stabilization of multimachine power systems viagenetic algorithms by Abdel-Magid, Y.L.

    Published 1999
    “…The power system operating at various conditions is treated as a finite set of plants. The problem of selecting the parameters of power system stabilizers which simultaneously stabilize this set of plants is converted to a simple optimization problem which is solved by a genetic algorithm with an eigenvalue-based objective function. …”
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  17. 57

    Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

    Published 2022
    “…The esc-edRVFL is identified as the best-performing algorithm through a comprehensive evaluation of 31 UCI datasets.…”
  18. 58

    Evolutionary algorithm for predicting all-atom protein structure by Mansour, Nashat

    Published 2011
    “…This algorithm produces a 3D structure of the whole protein, including back-bone and side-chain atoms, by minimizing the energy function associated with the structure. …”
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  19. 59

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

    Published 2006
    “…A series of experiments are performed to evaluate the efficiency of the algorithms. …”
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