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  1. 1

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

    Published 2023
    “…Genetic algorithms are powerful optimizing techniques that are used successfully to solve problems in many different disciplines. …”
    Conference paper
  2. 2

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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    Thesis
  3. 3

    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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    Undergraduates Project Papers
  4. 4

    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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    Article
  5. 5

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

    Published 2019
    “…Optimization is an important process in solving most engineering problems. …”
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    Thesis
  6. 6

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

    Published 2022
    “…Another type of algorithm is called numerical algorithms. These algorithms were built specifically to address numerical optimization problems. …”
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    Thesis
  7. 7

    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
  8. 8

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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    Article
  9. 9

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

    Published 2015
    “…Later, binary gravitational search algorithm (BGSA) is designed to solve discrete optimization problems. …”
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    Conference or Workshop Item
  10. 10

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

    Published 2024
    “…Furthermore, the original DA is only suitable for solving continuous optimization problems. Although there is a binary version of the algorithm, it cannot be directly used for solving discrete optimization problems like the Traveling Salesman Problem (TSP). …”
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    Thesis
  11. 11

    Solving multi-task optimization problems using the sine cosine algorithm by Kamal Z., Zamli, Kader, Md. Abdul

    Published 2022
    “…Often, optimization problems are solved using metaheuristic algorithms which provide good enough solution within reasonable execution time and limited resources. …”
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    Conference or Workshop Item
  12. 12

    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
    “…Finally, SGA is proposed to solve very extensive test problems including IoT optimization problems. …”
    Article
  13. 13

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

    Published 2021
    “…Algorithm is widely used in various areas due to its ability to solve classes of problems. …”
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    Article
  14. 14

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…Apart from the size of the optimization problem, how the swapping interval affects the dynamic optimization by the ant algorithms is also investigated. …”
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    Thesis
  15. 15

    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
  16. 16

    Review on bio-inspired algorithms approach to solve assembly line balancing problem by Noorazliza, Sulaiman, Junita, Mohamad Saleh, Nor Rokiah Hanum, Md. Haron, Z. A., Kamaruzzaman

    Published 2019
    “…Bio-inspired algorithms that have been developed by mimicking the biological phenomenon of nature have been widely applied to solve many real-world problems. …”
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    Conference or Workshop Item
  17. 17

    A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega) by Tan, Tun Tai

    Published 2009
    “…Genetic Algorithms (GAs) are a powerful stochastic search in solving optimization problems. …”
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    Final Year Project Report / IMRAD
  18. 18

    A Kalman Filter Approach for Solving Unimodal Optimization Problems by Zuwairie, Ibrahim, Nor Hidayati, Abdul Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Ibrahim, Shapiai, Sophan Wahyudi, Nawawi, Mohd Saberi, Mohamad

    Published 2015
    “…To evaluate the performance of the SKF algorithm in solving unimodal optimization problems, it is applied unimodal benchmark functions of CEC 2014 for real-parameter single objective optimization problems. …”
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    Article
  19. 19

    Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad

    Published 2016
    “…This paper compares the performances of the African Buffalo Optimization (ABO), hybrid Honey Bee Mating Optimization (HBMO) and the Lin-Kernighan (LKH) algorithms for solving the problems of the Symmetric Travelling Salesman’s Problems. …”
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    Article
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