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  1. 1

    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm by Mohammed Abdullah, Abdullah Nasser

    Published 2018
    “…In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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    Thesis
  2. 2

    Lévy mutation in artificial bee colony algorithm for gasoline price prediction by Mustaffa, Zuriani, Yusof, Yuhanis

    Published 2012
    “…In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. …”
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    Conference or Workshop Item
  3. 3

    NEXT-HOUR ELECTRICITY PRICE FORECASTING USING LEAST SQUARES SUPPORT VECTOR MACHINE AND GENETIC ALGORITHM by Razak I.A.W.A., Abidin I.Z., Siah Y.K., Sulaima M.F.

    Published 2023
    “…At the same time, the LSSVM parameters were optimized by GA to obtain accurate forecasts. …”
    Article
  4. 4

    Gradient method with multiple damping for large-scale unconstrained optimization by Sim, Hong Seng, Leong, Wah June, Chen, Chuei Yee

    Published 2019
    “…Finally, numerical results show that the proposed algorithm performs better than some well-known CG-based methods.…”
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    Article
  5. 5

    Open phase fault-tolerant support vector machine predictive power control for six-phase induction generator WECS by Hamoudi Y., Abdolrasol M.G.M., Amimeur H., Hassaini F., Ker P.J., Ustun T.S.

    Published 2025
    “…Then, open-phase localization is achieved using the Support Vector Machine (SVM) with hyperparameter Bayesian Optimization (BO). …”
    Article
  6. 6

    Improved Direct Torque Control (DTC) Performances Of Induction Machine Using Cascaded H-Bridge Multilevel Inverter by Ramahlingam, Sundram

    Published 2017
    “…The proposed DTC control algorithm can be optimally executed at high computation rate by totally using C-coding with DS1104 controller board. …”
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    Thesis
  7. 7
  8. 8

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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    Article
  9. 9
  10. 10

    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
  11. 11

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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    Thesis
  12. 12

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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    Thesis
  13. 13

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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    Thesis
  14. 14

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. …”
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    Book Chapter
  15. 15

    Migrating Birds Optimization based Strategies for Pairwise Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

    Published 2015
    “…For pairwise testing, test cases are designed to cover all possible pair combinations of input parameter values at least once. In this paper, we investigate the adoption of Migrating Birds Optimization (MBO) algorithm as a strategy to find an optimal solution for pairwise test data reduction. …”
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    Conference or Workshop Item
  16. 16

    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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    Article
  17. 17

    Hybrid Migrating Birds Optimization Strategy for t-way Test Suite Generation by Hasneeza, L. Zakaria, Kamal Z., Zamli, Fakhrud, Din

    Published 2019
    “…This paper presents the implementation of meta-heuristic search algorithms that are Migrating Birds Optimization (MBO) algorithm and Genetic Algorithm (GA) hybrid to a t-way test data generation strategy. …”
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  18. 18

    Nature-inspired parameter controllers for ACO-based reactive search by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2015
    “…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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    Article
  19. 19

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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    Article
  20. 20

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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    Undergraduates Project Papers