Search Results - different optimisation algorithm

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  1. 1

    Application of the bees algorithm for constrained mechanical design optimisation problem by Kamaruddin, Shafie, Abd Latif, Mohd Arif Hafizi

    Published 2019
    “…The Bees Algorithm is considered as one of the best optimisation algorithms because it has been successfully solved different type optimisation problem from in various field. …”
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    Article
  2. 2

    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…However, the performance of system is expected to be different from different algorithm.…”
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    Monograph
  3. 3

    Optimisation of vehicle routing problem with time windows using Harris Hawks optimiser by Chai, S. W., Kamaluddin, M. R., Ab Rashid, M. F. F.

    Published 2022
    “…This problem has been widely studied and optimised using different methods. Since the performance of algorithms in different problems is dissimilar, the study to optimise the VRPTW is ongoing. …”
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    Article
  4. 4

    Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm by Muhammad Arif, Abdullah

    Published 2019
    “…For optimisation purpose, this research proposed a relatively new algorithm called the Moth-Flame Optimisation (MFO). …”
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    Thesis
  5. 5

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. …”
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    Thesis
  6. 6

    Optimisation of energy efficient hybrid flowshop scheduling problem using firefly algorithm by M. F. F., Ab Rashid, Mohd Abdul, Hadi Osman

    Published 2020
    “…The optimisation results indicated that the FA outperformed Ant Colony Optimisation, Particle Swarm Optimisation and Artificial Bee Colony algorithms in majority of the problems. …”
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    Conference or Workshop Item
  7. 7

    Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm by Kamaruddin, Shafie, Ridzuan, Arman Hilmi, Sukindar, Nor Aiman

    Published 2025
    “…The focus of this study is to determine the optimum input parameter of the 3D printer using the Bees Algorithm (BA). This study uses the Bees Algorithm to predict the best combination parameters to optimise the surface roughness of parts printed by a fused deposition modelling (FDM) machine. …”
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    Book Chapter
  8. 8

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…At the same time, the total ethanol formation is 0.19 g/l and 0.03 g/l lower than the exponential feeding and genetic algorithm, respectively. In other cases of different initial yeast and substrate concentrations, the proposed algorithm in general outperforms the exponential feeding profile while produces comparable results to the genetic algorithm. …”
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    Thesis
  9. 9

    Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic by Sa'ad, Suleiman, Abdullah, Muhammed, Abdullah, Azizol, Ayob, Fahrul Hakim

    Published 2022
    “…In the past few years nature-inspired algorithms are experiencing rapid growth where most optimisation problems in different domains are addressed using it. …”
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    Article
  10. 10

    A hyper-heuristic cost optimisation approach for Scientific Workflow Scheduling in cloud computing by Alkhanak, Ehab Nabiel, Lee, Sai Peck

    Published 2018
    “…This can be done by employing different meta-heuristic algorithms in order to utilise their strengths for each scenario. …”
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    Article
  11. 11

    Multi-Objective Discrete Particle Swarm Optimisation Algorithm for Integrated Assembly Sequence Planning and Assembly Line Balancing by M. F. F., Ab Rashid, Hutabarat, Windo, Tiwari, Ashutosh

    Published 2016
    “…A computational experiment with 51 test problems at different difficulty levels was used to test the multi-objective discrete particle swarm optimisation performance compared with the existing algorithms. …”
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    Article
  12. 12
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    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…Therefore, this research also investigates and compares the two different VSIs that are widely used to determine the most suitable VSI that gives much better optimisation results. …”
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    Thesis
  14. 14
  15. 15

    Smart grid: Bio-inspired algorithms energy distributions for data centers by Woo, Yu Hang

    Published 2025
    “…This project proposes and evaluates three bio-inspired and evolutionary algorithms for VM allocation and migration: Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO), and a Modified Genetic Algorithm (MGA). …”
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    Final Year Project / Dissertation / Thesis
  16. 16

    The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga by Dada Emmanuel, Gbenga

    Published 2016
    “…Also, many of these PSO algorithms employed hybrid methods that integrate other optimisation algorithms with the standard PSO. …”
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    Thesis
  17. 17

    A modified flower pollination algorithm and carnivorous plant algorithm for solving engineering optimization problem by Ong, Kok Meng

    Published 2021
    “…Flower pollination algorithm (FPA) is a biomimicry optimisation algorithm inspired by natural pollination. …”
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    Thesis
  18. 18

    Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation by Choong, Shin Siang

    Published 2019
    “…Approaches for solving combinatorial optimisation problems can be separated into two main sub-classes, i.e. exact and approximation algorithms. …”
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    Thesis
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    An improvement of back propagation algorithm using halley third order optimisation method for classification problems by Abdul Hamid, Norhamreeza

    Published 2020
    “…This algorithm utilises first order optimisation method namely Gradient Descent (GD) method which attempts to minimise the error of network. …”
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    Thesis