Search Results - (( using adaptive problem algorithm ) OR ( simulation optimization based algorithm ))

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  1. 1

    Opposition-based learning simulated kalman filter for Numerical optimization problems by Mohd Falfazli, Mat Jusof

    Published 2016
    “…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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    Research Book Profile
  2. 2

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

    Published 2019
    “…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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    Thesis
  3. 3

    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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    Article
  4. 4

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…The increasing interest among researchers in the application of metaheuristic algorithms for search optimization has resulted in notable progress, especially in tackling single objective optimization problems. …”
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    Thesis
  5. 5

    Adaptive DNA computing algorithm by using PCR and restriction enzyme by Watanabe, Shinpei, Tsuboi, Yusei, Ibrahim, Zuwairie, Yamamoto, Tsuneto, Ono, Osamu

    Published 2004
    “…Finally, we go on to propose applying adaptive algorithm to the chemistry experiment which used the actual DNA molecules for soiving B universal problem.…”
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    Book Section
  6. 6

    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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    Thesis
  7. 7

    Exponentially adaptive sine-cosine algorithm for global optimization by Mohd Falfazli, Mat Jusof, Nurul Amira, Mhd Rizal, Ahmad Azwan, Abdul Razak, Shuhairie, Mohammad, Ahmad Nor Kasruddin, Nasir

    Published 2019
    “…It is widely used to solve various optimization problems. However the algorithm performance in terms of accuracy is not at optimum level. …”
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    Conference or Workshop Item
  8. 8

    An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem by Kader, Md. Abdul, Zamli, Kamal Z., Alkazemi, Basem Yousef

    Published 2022
    “…Emperor Penguin Optimizer (EPO) is a recently developed population-based meta-heuristic algorithm that simulates the huddling behavior of emperor penguins. …”
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    Article
  9. 9

    Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization by Kamal Z., Zamli

    Published 2018
    “…Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). …”
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    Conference or Workshop Item
  10. 10

    Enhanced utility accrual scheduling algorithms for adaptive real time system. by Othman, Muhammad Fauzan, Ahmad, Idawaty

    Published 2009
    “…We compared the performances of these algorithms by using discrete event simulation. Results: The proposed PUAS algorithm achieved the highest accrued utility for the entire load range. …”
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    Article
  11. 11

    Estimation-based Metaheuristics: A New Branch of Computational Intelligence by Nor Hidayati, Abd Aziz, Zuwairie, Ibrahim, Saifudin, Razali, Nor Azlina, Ab. Aziz

    Published 2016
    “…The experimental results show that the estimation-based metaheuristic is a promising approach to solving global optimization problem and demonstrates a competitive performance to some well-known metaheuristic algorithms…”
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    Conference or Workshop Item
  12. 12

    Fpga Implementation Of Metaheuristic Optimization Algorithm by Phuah, Soon Eu

    Published 2022
    “…Metaheuristic algorithms are gaining popularity amongst researchers due to their ability to solve nonlinear optimization problems as well as the ability to be adapted to solve a variety of problems. …”
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    Undergraduates Project Papers
  13. 13

    FPGA implementation of metaheuristic optimization algorithm by Nurul Hazlina, Noordin, Phuah, Soon Eu, Zuwairie, Ibrahim

    Published 2023
    “…Metaheuristic algorithms are gaining popularity amongst researchers due to their ability to solve nonlinear optimization problems as well as the ability to be adapted to solve a variety of problems. …”
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    Article
  14. 14

    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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    Thesis
  15. 15

    Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO) by Liew, Jia Hun

    Published 2024
    “…Adapting the Gaussian gas plume model in the simulation provides the experiment with a realistic optimization problem for GiPSO to optimize in the simulation, where we can test the engagement of dynamically challenging optimization problems such as gas plume dispersions. …”
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    Thesis
  16. 16

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    Published 2019
    “…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
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    Thesis
  17. 17

    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    “…The main motivations for investigating IWD algorithm are: (i) IWD has been successfully employed to solve many optimization problems. …”
    thesis::doctoral thesis
  18. 18

    Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread by Roshahliza, M. Ramli, Noor, Ali O. Abid, Salina, Abdul Samad

    Published 2016
    “…The simulation results showed the capability of proposed algorithm to eliminate different types of environmental noise with fast convergence, reduction in computational complexity and improvement in signal-to-noise ratio when compared with an equivalent system using a single adaptive algorithm. …”
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    Conference or Workshop Item
  19. 19

    An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz by Nor Azlina, Ab. Aziz

    Published 2017
    “…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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    Thesis
  20. 20

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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    Thesis