Search Results - "meta heuristic algorithm"

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  1. 1

    Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization by Kamal Z., Zamli

    Published 2018
    “…Many meta-heuristic algorithms have been developed to date (e.g. …”
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    A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem by Nurul Asyikin, Zainal, Kamal Z., Zamli, Fakhrud, Din

    Published 2020
    “…To date, there are much increasing trends on adopting parameter free meta-heuristic algorithms for solving general optimization problems. …”
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    An Improved Jaya Algorithm-Based Strategy for T-Way Test Suite Generation by Abdullah, Nasser, Hujainah, Fadhl, Al-Sewari, Abdulrahman A., Kamal Z., Zamli

    Published 2020
    “…T-way testing strategies adopt the meta-heuristic algorithms to generate the smallest/optimal test suite. …”
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    Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences by Adnan Ashraf, Sobia Pervaiz, Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
    “…To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. Population initialization plays a prominent role in meta-heuristic algorithms for the problem of optimization. …”
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    A review of assembly line balancing optimisation with energy consideration using meta-heuristic algorithms by Mohd Fadzil Faisae, Ab Rashid, Ariff Nijay, Ramli

    Published 2021
    “…The selected articles were limited to problems solved using meta-heuristic algorithms. The review mainly focusses on the soft computing aspect such as problem variant, optimisation objectives, energy modelling and optimisation algorithm for ALB with energy consideration. …”
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    PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

    Published 2019
    “…Meta-heuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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    An application barnacles mating optimizer for forecasting of full load electrical power output by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Bariah, Yusob, Ferda, Ernawan

    Published 2020
    “…The application of meta-heuristic algorithms in addressing numerous real-world problems have been proven to be effective. …”
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    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

    Published 2014
    “…In order to help engineers make a sound decision on the selection amongst the best meta-heuristic algorithms for the problem at hand, there is a need to assess the performance of each algorithm against common case studies. …”
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    Recent advances in meta-heuristic algorithms for training multilayer perceptron neural networks by Al-Asaady, Maher Talal, Mohd Aris, Teh Noranis, Mohd Sharef, Nurfadhlina, Hamdan, Hazlina

    Published 2025
    “…However, conventional training techniques such as Gradient Descent (GD) and Backpropagation (BP) often suffer from early convergence, dependence on initial parameters, and susceptibility to local optima, limiting their efficiency in complex, high-dimensional problems. Meta-heuristic algorithms (MHAs) offer a promising alternative as practical approaches for training ANNs, providing global search capabilities, robustness, and improved computational efficiency. …”
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    Locust- inspired meta-heuristic algorithm for optimising cloud computing performance by Fadhil, Mohammed Alaa

    Published 2023
    “…The simulation results demonstrate that the proposed algorithm outperforms existing heuristic and meta-heuristic algorithms, including the benchmarking algorithm (LACE). …”
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    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem by Kader, Md. Abdul, Zamli, Kamal Z., Alkazemi, Basem Yousef

    Published 2022
    “…Emperor Penguin Optimizer (EPO) is a recently developed population-based meta-heuristic algorithm that simulates the huddling behavior of emperor penguins. …”
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    Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms by Chong K.L., Lai S.H., Ahmed A.N., Zaafar W.Z.W., Rao R.V., Sherif M., Sefelnasr A., El-Shafie A.

    Published 2023
    “…Biomimetics; Computational efficiency; Dams; Electric load dispatching; Heuristic algorithms; Heuristic methods; Hydroelectric power; Hydroelectric power plants; Irrigation; Mathematical programming; Scheduling; Structural design; Water distribution systems; Water resources; Water supply; Application problems; Hydro-power generation; Meta heuristic algorithm; Non-differentiability; Problem formulation; Reservoir optimal operation; Reservoir optimizations; Scientific discipline; Reservoirs (water)…”
    Article
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    Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms by Chong K.L., Lai S.H., Ahmed A.N., Jaafar W.Z.W., Rao R.V., Sherif M., Sefelnasr A., El-Shafie A.

    Published 2023
    “…Biomimetics; Computational efficiency; Dams; Electric load dispatching; Heuristic algorithms; Heuristic methods; Hydroelectric power; Hydroelectric power plants; Irrigation; Mathematical programming; Scheduling; Structural design; Water distribution systems; Water resources; Water supply; Application problems; Hydro-power generation; Meta heuristic algorithm; Non-differentiability; Problem formulation; Reservoir optimal operation; Reservoir optimizations; Scientific discipline; Reservoirs (water)…”
    Article
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    New heuristic function in ant colony system for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Alobaedy, Mustafa Muwafak

    Published 2012
    “…Job scheduling problem classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This paper focuses on enhancing the heuristic function where information about recent ants’ discoveries will be taken into account.Experiments were conducted using a simulator with dynamic environment features to mimic the grid environment.Results show that the proposed enhanced algorithm produce better output in term of utilization and make span.…”
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