Search Results - (( initial solution method algorithm ) OR ( using optimization strategy algorithm ))

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  1. 1

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…The algorithm includes (i) a population update strategy which improves the movement of hawks in the search space, (ii) a parameter adjusting strategy to control the transition between exploration and exploitation, and (iii) a population generating method in producing the initial candidate solutions. …”
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  2. 2

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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  3. 3

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Meanwhile, MAFIRO differs from AFIRO in terms of the iteration search strategy. These three algorithms are called in short as FIR optimizers (FIROs). …”
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  11. 11

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Meanwhile, MAFIRO differs from AFIRO in terms of the iteration search strategy. These three algorithms are called in short as FIR optimizers (FIROs). …”
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    Using artificial intelligence search in solving the camera placement problem by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P.

    Published 2022
    “…In general, artificial intelligence search strategies are extensively used in solving discrete optimization problems. …”
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  15. 15

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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  16. 16

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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  17. 17

    A Dual Recurrent Neural Network-based Hybrid Approach for Solving Convex Quadratic Bi-Level Programming Problem by WATADA, J., ROY, A., LI, J., WANG, B., WANG, S.

    Published 2020
    “…Moreover, the GA can quickly reach the global optima and can search without becoming stuck to the local optimal. Additionally, by choosing desirable initialization of parameters, the proposed algorithm reaches the optimum with higher accuracy. …”
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  18. 18

    Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm by Talib, Nihad Hasan

    Published 2020
    “…The solution strategy started in its initial input and process to find effective stations that can serve the railway monitoring system well. …”
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  19. 19

    Optimizing wavelet neural networks using modified cuckoo search for multi-step ahead chaotic time series prediction by Ong, Pauline, Zainuddin, Zarita

    Published 2019
    “…The resulting solutions from the MCSA are then used as the initial translation vectors for the WNNs. …”
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  20. 20

    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

    Published 2025
    “…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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