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  1. 1
    Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm

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

    Published 2018
    “…Addressing these aforementioned issues and complementing the existing sequence based strategies such as t-SEQ, Sequence Covering Array Generator and Bee Algorithm, this thesis presents a unified strategy based on the new meta-heuristic algorithm, called the Elitist Flower Pollination Algorithm (eFPA). …”
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  2. 2
    Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines

    Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines by Noroziroshan, Alireza

    Published 2009
    “…It confirms that the proposed genetic algorithm procedure is able to tackle the problem complexity and reach to optimal solutions in different production strategies. …”
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  3. 3
    Sequence t-way test generation using the barnacles mating optimizer algorithm

    Sequence t-way test generation using the barnacles mating optimizer algorithm by Kamal Z., Zamli, Kader, Md. Abdul

    Published 2021
    “…More precisely, we focus on the generation of test cases due to the ordering of inputs (or sequence) using the newly developed Barnacles Mating Optimizer (BMO) Algorithm. …”
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  4. 4
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    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
    “…To improve the performance of the swap sequence based PSO, this paper introduces an Enhanced Swap Sequence based PSO (Enhanced SSPSO) algorithm by integrating the strategies of the Expanded PSO (XPSO) in the swap sequence based PSO. …”
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  5. 5
    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
    “…This paper presents statistical analysis on the performance of Bees Algorithm against the other sequence t-way strategies, in order to generate test cases.…”
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  6. 6
    T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm

    T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm by Rahman, Mostafijur, Sultana, Dalia, Sabira, Khatun, M. F. M., Jusof, Syamimi Mardiah, Shaharum, Nurhafizah, Abu Talip Yusof, Qaiduzzaman, Khandker M., Hasan, Md. Hasibul, Rahman, Md. Mushfiqur, Hossen, Md. Anwar, Begum, Afsana

    Published 2019
    “…The reason is that the T-way sequence input interaction is NP-Hard problem. In this research, Fish Swarm algorithm is proposed to adapt with T-way sequence input interaction test strategy. …”
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  7. 7
    BASE: a bacteria foraging algorithm for cell formation with sequence data

    BASE: a bacteria foraging algorithm for cell formation with sequence data by Nouri, Hossein, Tang, Sai Hong, Baharudin, B. T. Hang Tuah, Mohd Ariffin, Mohd Khairol Anuar

    Published 2010
    “…In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. …”
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  8. 8
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…Hence, this research’s objective aimed to propose an optimization strategy based on Structural Modification and Optimizing Training Network for improving the lacking of accuracy of response in the chatbot application, to propose the algorithm enhancement to improve the current attention mechanism in the Attentive Sequence-to-Sequence model and the network’s training optimization of its inability to memorize the dialogue history, and lastly, to evaluate the accuracy of response of the proposed solution through data training on loss function and real data testing. …”
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  9. 9
    Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences

    Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences by Adnan Ashraf, Sobia Pervaiz, Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Danda B. Rawat

    Published 2021
    “…To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. …”
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  10. 10
    Process Sequencing Modeled as TSP with Precedence Constraints - A Genetic Algorithm Approach

    Process Sequencing Modeled as TSP with Precedence Constraints - A Genetic Algorithm Approach by N. M., Razali

    Published 2014
    “…The developed GA procedure improved the performance of the algorithm with less number of generations and less convergence time in achieving optimal solutions. …”
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  11. 11
    Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences

    Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences by Rajesvary Rajoo R., Salam R.A.

    Published 2024
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  12. 12
    A hybrid of differential search algorithm and flux balance analysis to: Identify knockout strategies for in silico optimization of metabolites production

    A hybrid of differential search algorithm and flux balance analysis to: Identify knockout strategies for in silico optimization of metabolites production by Daud K.M., Zalmiyah Zakaria, Zuraini Ali Shah, Mohd Saberi Mohamad, Safaai Deris, Omatu S., Juan Manuel Corchado Rodríguez

    Published 2018
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  13. 13
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Abd Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  14. 14
    On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems

    On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems by Mohammed Ahmed, Adeeb Ali

    Published 2020
    “…The optimization of the antenna selection and optimal transmission power with impact of pilot reuse sequences were achieved, by applying Newton’s method and the Lagrange multiplier. …”
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  15. 15
    Iteration strategy and ts effect towards the performance of population based metaheuristics

    Iteration strategy and ts effect towards the performance of population based metaheuristics by Nor Azlina, Ab. Aziz, Nor Hidayati, Abdul Aziz, Azlan, Abd Aziz, Tasiransurini, Abdul Rahman, Wan Zakiah, Wan Ismail, Zuwairie, Ibrahim

    Published 2020
    “…The finding shows that iteration strategy can influence the performance of an algorithm and the best iteration strategy is unique to its parent algorithm. …”
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  16. 16
    Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran

    Network reconfiguration and DG sizing incorporating optimal switching sequence for system improvement / Ola Subhi Waheed Badran by Ola Subhi , Waheed Badran

    Published 2018
    “…The obtained results demonstrate the effectiveness of the proposed strategy to determine the sequence path of switching operations, as well as the optimal network configuration and optimal generation output of DG units. …”
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  17. 17
    Solving assembly sequence planning using angle modulated simulated kalman filter

    Solving assembly sequence planning using angle modulated simulated kalman filter by Ainizar, Mustapa, Zulkifli, Md. Yusof, Asrul, Adam, Badaruddin, Muhammad, Zuwairie, Ibrahim

    Published 2018
    “…This paper presents an implementation of Simulated Kalman Filter (SKF) algorithm for optimizing an Assembly Sequence Planning (ASP) problem. …”
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  18. 18
    Development of intelligent evaluation system for product end-of-life selection strategy

    Development of intelligent evaluation system for product end-of-life selection strategy by Zakri, Ghazalli

    Published 2011
    “…This study integrates the travelling salesman problem with genetic algorithm (TSP-GA) for finding the optimal disassembly sequence and disassembling the EOL product. …”
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  19. 19
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Ab. Aziz, Nor Azlina, Ibrahim, Zuwairie, Mubin, Marizan, Nawawi, Sophan Wahyudi, Mohamad, Mohd Saberi

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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  20. 20
    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update

    Improving particle swarm optimization via adaptive switching asynchronous – synchronous update by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Marizan, Mubin, Sophan Wahyudi, Nawawi, Mohd Saberi, Mohamad

    Published 2018
    “…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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