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  1. 1
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
    Conference paper
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  2. 2
    An improved grey wolf with whale algorithm for optimization functions

    An improved grey wolf with whale algorithm for optimization functions by Asgher, Hafiz Maaz

    Published 2022
    “…The Grey Wolf Optimization (GWO) is a nature-inspired, meta-heuristic search optimization algorithm. …”
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  3. 3
    PSO-LFDE Algorithm on Constrained Real-Parameter Optimisation Test Functions

    PSO-LFDE Algorithm on Constrained Real-Parameter Optimisation Test Functions by Nafrizuan, Mat Yahya, Nur Iffah, Mohamed Azmi

    Published 2023
    “…The results indicated that the PSO-LFDE has achieved competitive results on the single-objective constrained real-parameter optimisation test functions as compared to PSO algorithm by Gaing. Thus, the PSO-LFDE is validated as a stable, well-designed algorithm and can be a functional alternative approach to deal with various single-objective constrained real-parameter optimisation problems.…”
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  4. 4
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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  5. 5
    Improved combined mutation clonal selection algorithm

    Improved combined mutation clonal selection algorithm by Paw J.K.S., Hen C.K., Yan K.W., Ann Y.S.

    Published 2023
    Conference paper
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  6. 6
    Impact of Balanced Exploration and Exploitation on High-dimensional Feature Selection with Hierarchical Whale Optimisation Algorithm

    Impact of Balanced Exploration and Exploitation on High-dimensional Feature Selection with Hierarchical Whale Optimisation Algorithm by Yab, Li Yu, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2024
    “…The HiWOA incorporates a two-phase strategy comprising a nonlinear control parameter based on the arcsine function and a hierarchical position-update mechanism adapted from the Grey Wolf Optimiser. …”
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  7. 7
    A new HMCR parameter of harmony search for better exploration

    A new HMCR parameter of harmony search for better exploration by Mansor, N.F., Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S.

    Published 2016
    “…As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. …”
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  8. 8
    A new HMCR parameter of harmony search for better exploration

    A new HMCR parameter of harmony search for better exploration by Nur Farraliza, Mansor, Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S

    Published 2015
    “…As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. …”
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  9. 9
    Ringed seal search for global optimization via a sensitive search model / Younes Saadi

    Ringed seal search for global optimization via a sensitive search model / Younes Saadi by Younes, Saadi

    Published 2018
    “…The proposed algorithm is characterized by a search model namely the sensitive search model, where the exploitation-exploration is adaptively balanced. …”
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  10. 10
    Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group

    Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group by Azali Saudi, Jumat Sulaiman

    Published 2014
    “…In this paper, a robust searching algorithm to generate path planning for mobile robot is proposed. …”
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  11. 11
    A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN

    A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN by BISWAS, KALLOL

    Published 2021
    “…The improvements of the original PSO algorithm are proposed by updating its exploitation phase by incorporating the GWO algorithm because of its strong exploitation capability and the exploration phase using a cellular automaton due to its ability to explore more area by constructing new neighbours. …”
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  12. 12
    Algorithm in the fluidized-bed reactor for the polymerization of propylene

    Algorithm in the fluidized-bed reactor for the polymerization of propylene by Zanil, Mohd Fauzi, Chan, K.O., Hussain, Mohd Azlan

    Published 2019
    “…The multiple searches is proposed in the exploration phase to evaluate the multi objective functions. …”
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  13. 13
    Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor

    Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor by Ramli, Mohamad Raziff, Abal Abas, Zuraida, Desa, Mohammad Ishak, Zainal Abidin, Zaheera, Al Azzam, Malik Bader Hasan

    Published 2019
    “…However, Bat Algorithm can be get trapped in a local minimum in some multi-dimensional functions. …”
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  14. 14
    Crossover and mutation operators of real coded genetic algorithms for global optimization problems

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…On another note, the drawback in CS is in locating the most stable conformation of a molecule with the minimum potential energy based on a mathematical function. …”
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  15. 15
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…Artificial Neural Networks (ANN) techniques, mostly Back-Propagation Neural Network (BPNN) algorithm has been used as a tool for recognizing a mapping function among a known set of input and output examples. …”
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  16. 16
    Solving large-scale problems using multi-swarm particle swarm approach

    Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

    Published 2018
    “…The proposed algorithm was tested on several test functions, with four different number of dimensions (100, 500, and 1000) it was evaluated in terms of performance efficiency and compared to standard PSO (SPSO), and mastersalve PSO algorithm. …”
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  17. 17
    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…A new mutation vector inspired by the two-opposite path (2-Opt) algorithm with adaptive mutation scalar (F ) and crossover rate (CR) control parameters were employed to enhance the exploration and exploitation phases of the proposed algorithm. …”
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  18. 18
    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method

    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

    Published 2024
    “…This oversight has created a theoretical gap in this research domain, underscoring the necessity for additional exploration and investigation to address this limitation. …”
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  19. 19
    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions

    Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

    Published 2022
    “…Instead of making purely random selections, the least frequently executed action is selected so that the GUI can be further explored. Q-Learning showed better results than the random exploration strategy but it also presented a weakness. …”
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  20. 20
    Midrange exploration exploitation searching particle swarm optimization with HSV-template matching for crowded environment object tracking

    Midrange exploration exploitation searching particle swarm optimization with HSV-template matching for crowded environment object tracking by Nurul Izzatie Husna, Muhamad Fauzi

    Published 2023
    “…In this algorithm, the worst particle will be relocating to a new position to ensure the concept of exploration and exploitation remains in the search space. …”
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