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  1. 1

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…Optimization is prevalent in almost all areas since a plethora of problems can be formulated as optimization problems. …”
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  2. 2

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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  3. 3

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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  4. 4

    A discrete simulated kalman filter optimizer for combinatorial optimization problems by Suhazri Amrin, Rahmad

    Published 2022
    “…A solution to a combinatorial optimization problem is frequently expressed in terms of a permutation, arrangement, or combination of elements. …”
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  5. 5

    Bees algorithm for Forest transportation planning optimization in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

    Published 2021
    “…Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. …”
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    Article
  6. 6

    Barnacles mating optimizer : a new bio-inspired algorithm for solving engineering optimization problems by M. H., Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Hamdan, Daniyal

    Published 2020
    “…This paper presents a novel bio-inspired optimization algorithm namely the Barnacles Mating Optimizer (BMO) algorithm to solve optimization problems. …”
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  7. 7

    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
    “…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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  8. 8

    Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems by Hyreil A., Kasdirin, N. M., Yahya, M. S. M., Aras, Tokhi, M. O.

    Published 2017
    “…This study presents a hybrid invasive weed firefly optimization (HIWFO) algorithm for global optimization problems. …”
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  9. 9

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. …”
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  10. 10
  11. 11

    The design and applications of the african buffalo algorithm for general optimization problems by Odili, Julius Beneoluchi

    Published 2017
    “…Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. …”
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  12. 12

    Tree physiology optimization in constrained optimization problem by Halim, A.H., Ismail, I.

    Published 2018
    “…This paper introduces Tree Physiology Optimization (TPO) algorithm for solving constrained optimization problem and compares the performance with other existing metaheuristic algorithms. …”
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    Article
  13. 13

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…During recent years, a new direction of research has emerged in optimization, with the research focus moving from the conventional static optimization problems to the dynamic optimization problems. …”
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  14. 14

    A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

    Published 2023
    “…Hence, a hybrid optimization algorithm called Artificial Bee Rabbit Optimization (ABRO) is proposed in this paper. …”
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  15. 15

    Barnacles mating optimizer: A new bio-inspired algorithm for solving engineering optimization problems by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Hamdan, Daniyal

    Published 2020
    “…This paper presents a novel bio-inspired optimization algorithm namely the Barnacles Mating Optimizer (BMO) algorithm to solve optimization problems. …”
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    Article
  16. 16
  17. 17

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…A new meta-heuristic optimization technique called the Slime Mould Algorithm (SMA) approach has a high convergence rate or a few iterations and superior optimization indices analyzed against other algorithms. …”
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  18. 18

    AN ENSEMBLE APPROACH OF METAHEURISTIC ALGORITHMS WITH PARABOLIC APPROXIMATION TO OPTIMIZE WELL PLACEMENT PROBLEM by ISLAM, JAHEDUL

    Published 2021
    “…Well placement optimization problem is a non-convex, multimodal, and discontinuous optimization problem. …”
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  19. 19

    Comparison of swarm intelligence algorithms for high dimensional optimization problems by Bashath, Samar, Ismail, Amelia Ritahani

    Published 2018
    “…Within a huge number of algorithms, selecting one algorithm among others for solving the high dimensional optimization problem is not an easily accomplished task. …”
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  20. 20

    The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

    Published 2025
    “…Therefore, proposing an efficient meta-heuristic to improve the inputs of the trainer in ML would be significant. In this study, a new idea centered on seed growth, Seed Growth Algorithm (SGA), as a conditional convergent evolutionary algorithm is proposed for optimizing several discrete and continuous optimization problems. …”
    Article