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  1. 1
    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 evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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  2. 2
    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
    “…However, very few strategies have been proposed for sequence-based t-way. 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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  3. 3
    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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  4. 4
    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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  5. 5
    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence

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

    Published 2011
    “…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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  6. 6
    Biogeography based optimization (BBO) algorithm to minimise non-productive time during hole-making process

    Biogeography based optimization (BBO) algorithm to minimise non-productive time during hole-making process by Tamjidy, Mehran, Paslar, Shahla, Baharudin, B. T. Hang Tuah, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar

    Published 2015
    “…The performance of proposed algorithm is evaluated based on various test problems adopted from the literature. …”
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  7. 7
    Development of an augmented reality based facility layout planning and optimization / Tan Chee Hau

    Development of an augmented reality based facility layout planning and optimization / Tan Chee Hau by Tan , Chee Hau

    Published 2020
    “…This study presents an augmented reality (AR) based facility layout planning (FLP) system with an optimization algorithm to assist facility layout designers in decision making. …”
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  8. 8
    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…This ordered series defines the travel sequence. Findings – The results of the SKF algorithm and the ssSKF algorithm will be evaluated to decide which algorithm is better at solving this type of problem. …”
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  9. 9
    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 procedure to select the task in sequence is based on “earliest position” techniques. …”
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  10. 10
    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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  11. 11
    An optimal mesh algorithm for remote protein homology detection

    An optimal mesh algorithm for remote protein homology detection by M. Abdullah, Firdaus, M. Othman, Razib, Kasim, Shahreen, Hashim, Rathiah, Hassan, Rohayanti, Asmuni, Hishammuddin, Taliba, Jumail

    Published 2011
    “…This paper also improves the quality of the multiple alignments via integration of a refinement algorithm. The framework of this paper began with datasets preparation on datasets from SCOP version 1.73, followed by multiple alignments of the protein sequences using CLUSTALW, MAFFT, ProbCons and T-Coffee for sequence-based multiple alignments and 3DCoffee, MAMMOTH-mult, MUSTANG and PROMALS3D for structural-based multiple alignments. …”
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  12. 12
    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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  13. 13
    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
    “…In conclusion, the proposed low-complexity iterative algorithm can be used to maximize the EE based on the maximum transmit power , where the noise power is less than the power of the received pilot sequence.…”
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  14. 14
    Multilevel optimization for dense motion estimation

    Multilevel optimization for dense motion estimation by Saaban, Azizan, Kalmoun, El Mostafa, Ibrahim, Haslinda, Ramli, Razamin, Omar, Zurni

    Published 2011
    “…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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  15. 15
    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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  16. 16
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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  17. 17
    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…Moreover, other than the memory-based feature, SED algorithm has fewer design parameters to be addressed and the independence of the gain sequence in the tuning process. …”
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  18. 18
    A review on particle swarm optimization algorithm and its variants to human motion tracking

    A review on particle swarm optimization algorithm and its variants to human motion tracking by Saini, S., Rambli, D.R.B.A., Zakaria, M.N.B., Sulaiman, S.B.

    Published 2014
    “…An attempt is made to provide a guide for the researchers working in the field of PSO based human motion tracking from video sequences. …”
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  19. 19
    Flock optimization algorithm-based deep learning model for diabetic disease detection improvement

    Flock optimization algorithm-based deep learning model for diabetic disease detection improvement by Balasubramaniyan, Divager, Husin, Nor Azura, Mustapha, Norwati, Mohd Sharef, Nurfadhlina, Mohd Aris, Teh Noranis

    Published 2024
    “…Hence, the research objective is to create an improved diabetic disease detection system using a Flock Optimization Algorithm-Based Deep Learning Model (FOADLM) feature modeling approach that leverages the PIMA Indian dataset to predict and classify diabetic disease cases. …”
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  20. 20
    Fuzzy adaptive emperor penguin optimizer for global optimization problems

    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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