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  1. 1
    An Interaction Strategy for Testing Software Product Lines using the Bat-inspired Algorithm

    An Interaction Strategy for Testing Software Product Lines using the Bat-inspired Algorithm by Alsariera, Yazan A., Mazlina, Abdul Majid, Kamal Z., Zamli

    Published 2015
    “…In line with the recent emergence of Search based Software Engineering (SBSE), this article presents a novel strategy for SPLs tests reduction using Bat-inspired algorithm (BA), called SPLBA. …”
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  2. 2
    TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm

    TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm by Kamal Z., Zamli, Alsariera, Yazan A.

    Published 2016
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  3. 3
    A Bat-inspired Strategy for T-Way Interaction Testing

    A Bat-inspired Strategy for T-Way Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A.

    Published 2015
    “…As part of the strategy implementation, researchers have started to turn into meta-heuristic algorithms in line with the emergence of the new field called Search based Software Engineering. …”
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  4. 4
    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
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  5. 5
    The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction

    The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

    Published 2023
    “…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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  6. 6
    SPLBA: an interaction strategy for testing software product lines using the bat-inspired algorithm

    SPLBA: an interaction strategy for testing software product lines using the bat-inspired algorithm by Kamal Z., Zamli, Yazan A., Alsariera, Mazlina, Abdul Majid

    Published 2015
    “…In line with the recent emergence of Search based Software Engineering (SBSE), this article presents a novel strategy for SPLs tests reduction using Bat-inspired algorithm (BA), called SPLBA. …”
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  7. 7
    Benchmarking of Bat-inspired Interaction Testing Strategy

    Benchmarking of Bat-inspired Interaction Testing Strategy by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B.

    Published 2016
    “…Complementing existing sampling strategies (i.e. in terms of dealing with interaction faults). To be specific, the interaction testing technique (refers to as t-way strategy) is based on interaction strength and is capable of dramatically reducing the number of test suite while ensuring practical coverage. …”
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  8. 8
    A bat-inspired testing strategy for generating constraints pairwise test suite

    A bat-inspired testing strategy for generating constraints pairwise test suite by Alsariera, Yazan A., Ahmed, Hussam Alddin Shihab, Alamri, Hammoudeh S., Mazlina, Abdul Majid, Kamal Z., Zamli

    Published 2018
    “…Complementing existing interaction based sampling strategies, pairwise testing has been extensively exploited resulting into many prototypes strategy implementations. …”
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  9. 9
    A refined differential evolution algorithm for improving the performance of optimization process

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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  10. 10
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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  11. 11
    Two level Differential Evolution algorithms for ARMA parameters estimatio

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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  12. 12
    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm

    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm by Salami, Momoh Jimoh Eyiomika, Tijani, Ismaila, Isqeel , Abdullateef Ayodele, Aibinu, Abiodun Musa

    Published 2013
    “…A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). …”
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  13. 13
    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes

    Crossover-first differential evolution for improved global optimization in non-uniform search landscapes by Teo, Jason Tze Wi, Mohd Hanafi Ahmad Hijazi, Hui, Keng Lau, Salmah Fattah, Aslina Baharum

    Published 2015
    “…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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  14. 14
    Reliably optimal PMU placement using disparity evolution-based genetic algorithm

    Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

    Published 2017
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  15. 15
    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy

    Differential evolution optimization algorithm based on generation systems reliability assessment integrated with wind energy by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Abdalla, Ahmed N.

    Published 2019
    “…This stuffy proposed a novel optimization method labeled the "Differential Evolution Optimization Algorithm" (DEOA) to assess the reliability of power generation systems (PGS). …”
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  16. 16
    Performance comparison of differential evolution and particle swarm optimization in constrained optimization

    Performance comparison of differential evolution and particle swarm optimization in constrained optimization by Iwan, Mahmud, Akmeliawati, Rini, Faisal, Tarig, Al-Assadi, Hayder M.A.A.

    Published 2012
    “…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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  17. 17
    A bat-inspired t-way strategy for mixed-strength test suite generation

    A bat-inspired t-way strategy for mixed-strength test suite generation by Ahmad, Yazan Sadeq Al Sariera

    Published 2017
    “…Owing to its effectiveness for bug finding, many researchers are turning to the sampling strategies based on input interaction, called t-way testing, where t indicates the interaction strength. …”
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    Thesis
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  18. 18
    Optimal HE-PWM inverter switching patterns using differential evolution algorithm

    Optimal HE-PWM inverter switching patterns using differential evolution algorithm by Muhammad Ikram, Mohd Rashid, Hiendro, Ayong, Anwari, Makbul

    Published 2012
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  19. 19
    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution

    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2014
    “…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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  20. 20
    Broadening selection competitive constraint handling algorithm for faster convergence

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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