Search Results - (( evolution optimization based algorithm ) OR ( using optimisation search algorithm ))

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  1. 1

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

    Published 2025
    “…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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    Article
  2. 2

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

    Published 2025
    “…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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    Article
  3. 3

    Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods by Kadhem, Athraa Ali

    Published 2017
    “…This study sought to examine the performance of three newly proposed techniques, for reliability assessment of the power systems, namely Disparity Evolution Genetic Algorithm (DEGA), Binary Particle Swarm Optimisation (BPSO), and Differential Evolution Optimization Algorithm (DEOA). …”
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    Thesis
  4. 4

    Dual level searching approach for solving multi objective optimisation problems using hybrid particle swarm optimisation and bats echolocation-inspired algorithms by Nafrizuan, Mat Yahya, A. R., Yusoff, Azlyna, Senawi, Tokhi, M. Osman

    Published 2019
    “…A dual level searching approach for multi objective optimisation problems using particle swarm optimisation and modified adaptive bats sonar algorithm is presented. …”
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  5. 5

    Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic by Sa'ad, Suleiman, Abdullah, Muhammed, Abdullah, Azizol, Ayob, Fahrul Hakim

    Published 2022
    “…In the past few years nature-inspired algorithms are experiencing rapid growth where most optimisation problems in different domains are addressed using it. …”
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    Parametric modelling of twin rotor system using chaotic fractal search algorithm by Tuan Abdul Rahman, Tuan Ahmad Zahidi

    Published 2016
    “…One of the latest optimisation algorithms is Stochastic Fractal Search (SFS) algorithm. …”
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    Conference or Workshop Item
  8. 8

    Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

    Published 2017
    “…In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. …”
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  9. 9

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…DE is developed based on an improved Genetic Algorithm and come with different strategies for faster optimization. …”
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    Conference or Workshop Item
  10. 10

    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising by Al-Dabbagh, Mohanad Dawood, Al-Dabbagh, Rawaa Dawoud, Raja Abdullah, Raja Syamsul Azmir, Hashim, Fazirulhisyam

    Published 2015
    “…The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. …”
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    Article
  11. 11

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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    Thesis
  12. 12

    A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem by Ong, Kok Meng

    Published 2021
    “…Flower pollination algorithm (FPA) is a biomimicry optimisation algorithm inspired by natural pollination. …”
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  13. 13

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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    A self-adaptive step-size search algorithm for the cardinality constrained portfolio optimisation problem by Zi, Xuan Loke, Say, Leng Goh, Jonathan Likoh Juis @ Juise

    Published 2024
    “…This paper proposes a Self-adaptive Step-size Search (SASS) algorithm to address a Cardinality Constrained Portfolio Optimisation Problem (CCPOP). …”
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    Proceedings
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    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The algorithm is a hybrid algorithm that operates using dual level search strategy that takes merits of a particle swarm optimisation algorithm and a modified adaptive bats sonar algorithm. …”
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    Thesis
  18. 18

    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

    Published 2010
    “…Using the optimised crossover scheme, the two parents produce the two new children: the Ochild (Optimum child) and the E-child (Exploratory child). …”
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  19. 19

    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

    Published 2015
    “…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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    Article
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