Search Results - "based metaheuristics algorithm"

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  1. 1

    On the exploration and exploitation in popular swarm-based metaheuristic algorithms by Hussain, Kashif, Mohd Salleh, Mohd Najib, Cheng, Shi, Shi, Yuhui

    Published 2018
    “…This study, therefore, performed in-depth empirical analysis by quantitatively analyzing exploration and exploitation of five swarm-based metaheuristic algorithms. The analysis unearthed explanations the way algorithms performed on numerical problems as well as on real-world application of classification using adaptive neuro-fuzzy inference system (ANFIS) trained by selected metaheuristics. …”
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    Article
  2. 2

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

    Published 2019
    “…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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    Thesis
  3. 3
  4. 4

    Task scheduling on computational grids using Gravitational Search Algorithm by Zarrabi, Amirreza, Samsudin, Khairulmizam

    Published 2014
    “…In this paper, Gravitational Search Algorithm (GSA), as one of the latest population-based metaheuristic algorithms, is used for task scheduling on computational Grids. …”
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    Article
  5. 5

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

    Published 2019
    “…The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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    Thesis
  6. 6

    African Buffalo Optimization by Odili, Julius Beneoluchi, M. N. M., Kahar

    Published 2016
    “…This paper presents an overview of major metaheuristic algorithms with the aim of providing a basis for the development of the African Buffalo Optimization algorithm which is a nature-inspired, population-based metaheuristic algorithm. Experimental results obtained from applying the novel ABO to solve a number of benchmark global optimization test functions as well as some symmetric and asymmetric Traveling Salesman’s Problems when compared to the results obtained from using other popular optimization methods show that the African Buffalo Optimization is a worthy addition to the growing number of swarm intelligence optimization techniques. …”
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    Article
  7. 7

    An enhanced simulated kalman filter algorithm and its application in adaptive beamforming by Lazarus, Kelvin, Nurul Hazlina, Noordin, Zuwairie, Ibrahim

    Published 2019
    “…In this paper, a population based metaheuristic algorithm named Simulated Kalman Filter with Modified Measurement (SKFMM) is proposed for adaptive beamforming application. …”
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    Conference or Workshop Item
  8. 8

    Meta-heuristic structure for multiobjective optimization case study: Green sand mould system by Ganesan, T., Elamvazuthi, I., KuShaari, K.Z., Vasant, P.

    Published 2014
    “…By these procedures, a novel chaos-based metaheuristic algorithm, the Chaotic Particle Swarm (Ch-PSO) is developed. …”
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    Book
  9. 9

    Automated Examination Timetabling System (AETSys) / Ariff Md Ab Malik by Md Ab Malik, Ariff, Haruddin, Hanitahaiza, Alwi, Anisah, Mohamed, Khainizam

    Published 2013
    “…This system has been developed based on a hybridization of local search-population based metaheuristic algorithms. The whole process of timetable construction can be divided into two major phases; (i) timetable development and (ii) timetable optimization. …”
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    Book Section
  10. 10

    Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

    Published 2017
    “…This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. MBO with elitism for solving CIT problem. …”
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    Article
  11. 11

    Combinatorial test suites generation strategy utilizing the whale optimization algorithm by Ali Abdullah, Hassan, Salwani, Abdullah, Kamal Zuhairi, Zamli, Rozilawati, Razali

    Published 2020
    “…The experimental results of the test-suite generation indicate that WOA produces competitive outcomes compared to some selected single-based and population-based metaheuristic algorithms.…”
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    Article
  12. 12

    A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

    Published 2019
    “…In this research, a novel swarm-based metaheuristic algorithm which depends on the behavior of nomadic people was developed, it is called ‘‘Nomadic People Optimizer (NPO)’’. …”
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    Article
  13. 13

    Selective chaotic maps Tiki-Taka algorithm for the S-box generation and optimization by Kamal Z., Zamli, Abdul Kader, ., Fakhrud Din, ., Alhadawi, Hussam S.

    Published 2021
    “…., ensuring the generated S-box is sufficiently robust against linear and differential cryptanalysis attacks), many chaos-based metaheuristic algorithms have been developed in the literature. …”
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    Article
  14. 14

    Component-wise analysis of metaheuristic algorithms for novel fuzzy-meta classifier by Talfur, Khasif Hussain

    Published 2018
    “…This research selected three commonly used swarm-based metaheuristic algorithms – Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Cuckoo Search (CS) – to perform component-wise analysis. …”
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    Thesis
  15. 15

    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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    Thesis
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