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  1. 1

    Multi-State Particle Swarm Optimization for Discrete Combinatorial Optimization Problem by Ismail, Ibrahim, Hamzah, Ahmad, Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Kamal, Khalil, Muhammad Arif, Abdul Rahim

    Published 2014
    “…The binary-based algorithms including the binary particle swarm optimization (BPSO) algorithm are proposed to solve discrete optimization problems. …”
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    Article
  2. 2

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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    Thesis
  3. 3

    Particle swarm optimization and spiral dynamic algorithm-based interval type-2 fuzzy logic control of triple-link inverted pendulum system : a comparative assessment by M. F., Masrom, N. M. A., Ghani, M. O., Tokhi

    Published 2021
    “…It is shown that the particle swarm optimization-based control mechanism performs better than the spiral dynamic algorithm-based control in terms of system stability, disturbance rejection and reduce noise. …”
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    Article
  4. 4

    Score Fusion Using Hybrid Bacterial Foraging Optimization And Particle Swarm Optimization (Bfo-Pso) For Hand-Based Multimodal Biometrics by Shanmugasundaram, Karthikeyan

    Published 2020
    “…Therefore, this research is focused on the hand-based multimodal biometric score fusion which incorporates the scores of hand-based multimodalities and the optimal weights using Hybrid Bacterial Foraging - Particle Swarm Optimization (HBF-PSO) algorithm.…”
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    Thesis
  5. 5

    Hybrid Improved Bacterial Swarm Optimization Algorithm for Hand-Based Multimodal Biometric Authentication System by Shanmugasundaram, Karthikeyan, Mohmed, Ahmad Sufril Azlan, Ruhaiyem, Nur Intan Raihana

    Published 2019
    “…This paper proposes a Hybrid Improved Bacterial Swarm (HIBS) optimization algorithm for the minimization of Equal Error Rate (EER) as a performance measure in a hand-based multimodal biometric authentication system. …”
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    Article
  6. 6

    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
    “…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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    Article
  7. 7

    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…The MOSI algorithms are based on the integration of single objective algorithms and multi-objective optimization (MOO) approach. …”
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    Article
  8. 8

    Improved particle swarm optimization by fast annealing algorithm by Bashath, Samar, Ismail, Amelia Ritahani

    Published 2019
    “…The proposed algorithm is meant to solve high dimensional optimization problems based on two strategies, which are utilizing the particle swarm optimization to define the global search area and utilizing the fast-simulated annealing to refine the visited search area. …”
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    Proceeding Paper
  9. 9

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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    Thesis
  10. 10

    On the exploration and exploitation in popular swarm-based metaheuristic algorithms by Hussain, Kashif, Mohd Salleh, Mohd Najib, Cheng, Shi, Shi, Yuhui

    Published 2018
    “…Among such algorithms are swarm-based methods like particle swarm optimization and ant colony optimization which are increasingly attracting new researchers. …”
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    Article
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    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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    Article
  13. 13

    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

    Published 2011
    “…Present paper intends to provide a detailed description of a new bio-inspired Metaheuristic Algorithm. Based on the detailed study of the Drosophila, the flowchart behaviour for the algorithm, code implementation, methodologies and simulation analysis, a novel Fly Optimization Algorithm (FOA) approach is presented. …”
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    Article
  14. 14

    Improving robot Darwinian particle swarm optimization using quantum-behaved swarm theory for robot exploration and communication / Duaa Mehiar by Duaa , Mehiar

    Published 2021
    “…Despite the significance of the Robotic Darwinian Particle Swarm Optimization (RDPSO) algorithm on swarm-robot exploration and communication, there remain notable gaps such as premature and slow convergence, collisions between robots, and communication breaks and constraints. …”
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    Thesis
  15. 15

    An Improved Multi-State Particle Swarm Optimization for Discrete Optimization Problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…Recently, a state-based algorithm called multi-state particle swarm optimization (MSPSO) has been proposed to solve discrete combinatorial optimization problems. …”
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    Conference or Workshop Item
  16. 16

    Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

    Published 2024
    “…In this study, MATLAB models of a DRL-based MPPT algorithm were developed, tested, and compared to simulation based on two established MPPT algorithms-the Particle Swarm Optimization (PSO), and the Perturb and Observe (P&O). …”
    Conference Paper
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    Document clustering based on firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2015
    “…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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    Article
  19. 19

    Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

    Published 2024
    “…The trained network is then applied to benchmark classification problems. Based on the experimental results, the optimized DA algorithm is a much better training algorithm for ANNs as compared to the usual gradient-descent backpropagation algorithm since the resultant ANNs trained by the optimized DA achieve higher accuracy. …”
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    Thesis
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