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  1. 1

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…An adaptive bats sonar algorithm is proposed for solving single objective optimisation problems. …”
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    Thesis
  2. 2

    Dual level searching approach for solving multi objective optimisation problems using hybrid particle swarm optimisation and bats echolocation-inspired algorithms by Nafrizuan, Mat Yahya, A. R., Yusoff, Azlyna, Senawi, Tokhi, M. Osman

    Published 2019
    “…A dual level searching approach for multi objective optimisation problems using particle swarm optimisation and modified adaptive bats sonar algorithm is presented. …”
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    Article
  3. 3

    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation by M. F. F., Ab Rashid

    Published 2013
    “…The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. …”
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    Thesis
  4. 4
  5. 5

    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
  6. 6

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

    Published 2019
    “…Furthermore, a case study was conducted to validate the proposed EE-ASP model and the performance of the optimisation algorithms. The MFO performance was compared with three frequently used meta-heuristics algorithms in ASP, namely Ant Colony Optimisation (ACO), Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO). …”
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    Thesis
  7. 7

    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
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    Optimization of multi-holes drilling path using particle swarm optimization by Najwa Wahida, Zainal Abidin

    Published 2022
    “…One way to improve the multi-hole drilling is by optimising the tool path in the process. This research aims to model and optimise multi-hole drilling problems using Particle Swarm Optimisation (PSO) algorithm. …”
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    Thesis
  10. 10

    An Improved VEPSO Algorithm for Multi-objective Optimisation Problems by Kamarul Hawari, Ghazali, Zuwairie, Ibrahim, Faradila, Naim, Kian, Sheng Lim, Salinda, Buyamin, Anita, Ahmad, Sophan Wahyudi, Nawawi, Norrima, Mokhtar

    Published 2015
    “…The vector evaluated particle swarm optimisation algorithm is widely used for such purpose, where this algorithm optimised one objective using one swarm of particles by the guidance from the best solution found by another swarm. …”
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    Book Chapter
  11. 11

    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

    Published 2010
    “…In this thesis, the OCGA is applied to some combinatorial optimisation problems, specically on single machine scheduling problems and vehicle routing problems. …”
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    Thesis
  12. 12

    Multi-objective optimisation of assembly line balancing type-e problem with resource constraints by Masitah, Jusop

    Published 2016
    “…Later, the optimisation algorithm will be tested and verified using test problems from literature. …”
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    Thesis
  13. 13

    Single-Solution Simulated Kalman Filter Algorithm for Global Optimisation Problems by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Mohd Saberi, Mohamad, Watada, Junzo

    Published 2016
    “…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm, and Genetic Algorithm (GA). …”
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    Article
  14. 14

    Optimised crossover genetic algorithm for capacitated vehicle routing problem by Nazif, Habibeh, Lee, Lai Soon

    Published 2012
    “…The proposed algorithm uses an optimised crossover operator designed by a complete undirected bipartite graph to find an optimal set of delivery routes satisfying the requirements and giving minimal total cost. …”
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    Article
  15. 15
  16. 16

    Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

    Published 2018
    “…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). …”
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    Article
  17. 17

    Single-solution Simulated Kalman Filter algorithm for global optimisation problems by Abdul Aziz, N.H., Ibrahim, Z., Ab Aziz, N.A., Mohamad, M.S., Watada, J.

    Published 2018
    “…The proposed ssSKF algorithm is tested using the 30 benchmark functions of CEC 2014, and its performance is compared to that of the original SKF algorithm, Black Hole (BH) algorithm, Particle Swarm Optimisation (PSO) algorithm, Grey Wolf Optimiser (GWO) algorithm and Genetic Algorithm (GA). …”
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    Article
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    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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    Monograph
  20. 20

    Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II by Masitah, Jusop, M. F. F., Ab Rashid

    Published 2016
    “…Six benchmark problems have been used to test the optimisation algorithm and the results are compared to multi-objective genetic algorithm (MOGA) and hybrid genetic algorithm (HGA). …”
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    Article