Search Results - parallel solution ((machine algorithm) OR (((bees algorithm) OR (based algorithm))))

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  1. 1
    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This means that it spends a long time for the bees algorithm converge the optimum solution. In this study, the parallel bees algorithm technique is proposed for overcoming of this issue. …”
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  2. 2
    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources

    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources by Abed, Munther H., Mohd Nizam, Mohmad Kahar

    Published 2023
    “…The single-based metaheuristics replaces the mutation in the genetic algorithm. …”
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  3. 3
    Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm

    Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm by Mohd Abdul Hadi, Osman, Mohd Fadzil Faisae, Ab Rashid, Nik Mohd Zuki, Nik Mohamed, Muhammad Ammar, Nik Mu’tasim

    Published 2024
    “…This study addresses the hybrid flow shop scheduling with energy consideration (HFSE) problem, aiming to simultaneously optimize makespan and total energy consumption, two conflicting objectives. An Artificial Bee Colony (ABC) algorithm is proposed as an effective solution methodology for tackling the HFSE problem. …”
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  4. 4
    Flexible job shop scheduling using priority heuristics and genetic algorithm

    Flexible job shop scheduling using priority heuristics and genetic algorithm by Farashahi, Hamid Ghaani

    Published 2010
    “…The job shop scheduling is very common in practice and uniform machines (parallel machines with different speeds) have been used in job shop environment for flexibility. …”
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  5. 5
    Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem

    Fast Finite Difference Time Domain Algorithms for Solving Antenna Application Problem by Hasan, Mohammad Khatim

    Published 2008
    “…Based on experimental results and complexity analysis, these new sequential and parallel algorithms are compared with the standard sequential and parallel FDTD algorithms, respectively. …”
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  6. 6
    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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  7. 7
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…MEMPHA, a hypergraphs-based model, aims to aspire to the challenge by providing topology modelling of the target parallel machine and application modelling of the parallel application, which is hypergraph-based model, to abstract the details of HPAs. …”
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  8. 8
    Parallel block methods for solving higher order ordinary differential equations directly

    Parallel block methods for solving higher order ordinary differential equations directly by Omar, Zurni

    Published 1999
    “…Hence, the development of parallel algorithms to suit these machines becomes essential. …”
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  9. 9
    Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE)

    Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE) by Alias, Norma, Islam, Md. Rajibul

    Published 2010
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  10. 10
    Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach

    Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach by Quadros, Jaimon Dennis, Khan, Sher Afghan, T., Prashanth

    Published 2021
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  11. 11
    Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization

    Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

    Published 2022
    “…Based on the optimization results, the MFO outperformed other comparison algorithms for the mean fitness and also the best fitness. …”
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  12. 12
    Process Planning Optimization In Reconfigurable Manufacturing Systems

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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  13. 13
    A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA)

    A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA) by Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

    Published 2024
    “…The optimization result was compared with well-established algorithms, the Pareto Envelope-based Selection Algorithm II (PESA2), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), and new algorithms, Multi-Objective Grasshopper Optimization Algorithm (MOGOA) and Multi-Objective Ant Lion Optimizer (MOALO). …”
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  14. 14
    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery

    A parallel ensemble learning model for fault detection and diagnosis of industrial machinery by Shing, Chiang Ta, Mohammed Al-Andoli, Mohammed Nasser, Kok, Swee Sim, Seera, Manjeevan, Chee, Peng Lim

    Published 2023
    “…The base learners adopt a hybrid Back-Propagation (BP) and Particle Swarm Optimization (PSO) algorithms to exploit the corresponding local and global optimization capabilities for identifying optimal features and improving FDD performance. …”
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  15. 15
    A Distributed Memory Parallel Fourth-Order IADEMF Algorithm

    A Distributed Memory Parallel Fourth-Order IADEMF Algorithm by Mansor N.A., Zulkifle A.K., Alias N., Hasan M.K.

    Published 2023
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  16. 16
    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib

    Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

    Published 2019
    “…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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  17. 17
    Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm

    Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm by W., Safiei, Rahman, M. M., M.Y., Ali

    Published 2024
    “…For future study, other methods or algorithms can be applied in other machining processes to obtain optimum machining parameters.…”
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  18. 18
    Application of parallel ensemble Monte Carlo technique in charge dynamics simulation

    Application of parallel ensemble Monte Carlo technique in charge dynamics simulation by Umar, Roslan, -, Othman, -, A.P., -, Gopir

    Published 2008
    “…The use of Parallel Virtual Machine (PVM) standards when running the parallel algorithm of the ensemble MC simulation been proposed Some results of the development are also presented in this paper.…”
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  19. 19
    Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization

    Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization by Hazmi Wahab, Muhammad Hafizul

    Published 2024
    “…In order to address this, a novel solution called Decomposition-based Multi-objective Differential Evolution (MODE/D) is proposed. …”
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  20. 20
    Application of parallel ensemble Monte Carlo technique in charge dynamics simulation

    Application of parallel ensemble Monte Carlo technique in charge dynamics simulation by A. P. Othman, R. Umar, G. Gopir

    Published 2008
    “…We have proposed the use of Parallel Virtual Machine (PVM) standards when running the parallel algorithm of the ensemble MC simulation. …”
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