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  1. 1
    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
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  2. 2
    Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm

    Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Kendall, Graham, Chuah, Joon Huang

    Published 2018
    “…However, the complexity of these processes requires an expert system that involves swarm intelligence-based metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and Differential Evolution (DE) for simulation and optimization of the feeding trajectories. …”
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  3. 3
    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem

    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

    Published 2008
    “…Future, area that may be explored include the used of Ant Colony Optimization (ACO) which exploits the nature phenomenon of ants. …”
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  4. 4
    Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building

    Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2023
    “…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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  5. 5
    Dynamic smart grid communication parameters based cognitive radio network

    Dynamic smart grid communication parameters based cognitive radio network by Haider H.T., Muhsen D.H., Shahadi H.I., See O.H., Elmenreich W.

    Published 2023
    “…A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”
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  6. 6
    A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric conditions

    A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

    Published 2024
    “…Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
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  7. 7
    Optimized adaptive neuro-fuzzy inference system using metaheuristic algorithms: Application of shield tunnelling ground surface settlement prediction

    Optimized adaptive neuro-fuzzy inference system using metaheuristic algorithms: Application of shield tunnelling ground surface settlement prediction by Liu, Xinni, Hussein, Sadaam Hadee, Kamarul Hawari, Ghazali, Tung, Tran Minh, Yaseen, Zaher Mundher

    Published 2021
    “…The predictive models were various nature-inspired frameworks, such as differential evolution (DE), particle swarm optimization (PSO), genetic algorithm (GA), and ant colony optimizer (ACO) to tune the adaptive neuro-fuzzy inference system (ANFIS). …”
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  8. 8
    Reliably optimal PMU placement using disparity evolution-based genetic algorithm

    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

    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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  10. 10
    A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising

    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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  11. 11
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    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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  12. 12
    Broadening selection competitive constraint handling algorithm for faster convergence

    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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  13. 13
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
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  14. 14
    Ant colony optimization for rule induction with simulated annealing for terms selection

    Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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  15. 15
    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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  16. 16
    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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  17. 17
    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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  18. 18
    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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  19. 19
    Minimization of machining process sequence based on ant colony algorithm and conventional method

    Minimization of machining process sequence based on ant colony algorithm and conventional method by Abdullah, Haslina, Law, Boon Hui C., Zakaria, Mohamad Shukri

    Published 2023
    “…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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  20. 20
    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by H. ABDULLAH, H. ABDULLAH, C. LAW BOON HUI, C. LAW BOON HUI, M. S. ZAKARIA, M. S. ZAKARIA

    Published 2023
    “…Based on the simulation, the Ant Colony algorithm method is, on average, 10.8% better than conventional methods in reducing machining time. …”
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