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  1. 1

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

    Published 2016
    “…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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    Thesis
  2. 2

    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
  3. 3

    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. …”
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    Monograph
  4. 4
  5. 5

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

    Published 2016
    “…In this research, a Genetic-based Algorithm was used as an optimisation approach. …”
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  6. 6

    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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  7. 7

    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…Finally, an AHP was integrated with FA to form Firefly Analytical Hierarchy Algorithm (FAHA) to automatically calculate the weight of each objective function based on the load flow outputs followed by the optimisation process. …”
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    Thesis
  8. 8

    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

    Published 2019
    “…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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    Monograph
  9. 9

    A review of assembly line balancing optimisation with energy consideration using meta-heuristic algorithms by Mohd Fadzil Faisae, Ab Rashid, Ariff Nijay, Ramli

    Published 2021
    “…The selected articles were limited to problems solved using meta-heuristic algorithms. The review mainly focusses on the soft computing aspect such as problem variant, optimisation objectives, energy modelling and optimisation algorithm for ALB with energy consideration. …”
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    Article
  10. 10

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

    Published 2022
    “…The performance of PSO was then compared with other meta-heuristic algorithms, including Genetic Algorithm (GA) and Ant Colony Optimisation (ACO), Whale Optimisation Algorithm (WOA), Ant Lion Optimiser (ALO), Dragonfly Algorithm (DA), Grasshopper Optimisation Algorithm (GOA), Moth Flame Optimisation (MFO) and Sine Cosine Algorithm (SCA). …”
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    Thesis
  11. 11

    Completion time driven hyper-heuristic approach for optimisation of scientific workflow scheduling in cloud environment / Ehab Nabiel Mohammad by Ehab Nabiel , Mohammad

    Published 2018
    “…Thus, the main objective of this research is to propose a Completion Time Driven Hyper-Heuristic (CTDHH) approach for cost optimisation of SWFS in a cloud environment. …”
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  12. 12

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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    Thesis
  13. 13

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

    Published 2022
    “…Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisa­tion Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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    Thesis
  14. 14

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…A new emerging nature-inspired algorithm named Bacterial Foraging Optimisation Algorithm (BFOA) that mimics the foraging behaviour of E. coli bacteria has drawn lots of attention from other researchers due to its high convergence rate and global search capability compared to others. …”
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  15. 15

    Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

    Published 2024
    “…In this study, a new optimisation algorithm termed Hybrid Evolutionary-Barnacles Mating Optimisation (HEBMO) was initially formulated to solve optimisation problems. …”
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  16. 16

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

    Published 2023
    “…The proposed deep reinforcement learning algorithm, which integrates an artificial neural network with traditional reinforcement learning, was formulated based on the optimisation objective by manipulating only the substrate feeding rate. …”
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    Genetic algorithm for control and optimisation of exothermic batch process by Tan, Min Keng

    Published 2013
    “…As such, another approach, GA is proposed to optimise the productivity without referring to a predetermined profile, namely genetic algorithm optimiser (GAO). …”
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  19. 19

    Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm by Noor Azam, Muhammad Harith, Ridzuan, Farida, Mohd Sayuti, M Norazizi Sham

    Published 2023
    “…Therefore, this research proposed a new method for optimising cover audio selection for audio steganography using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which falls under the MOEA Pareto dominance paradigm. …”
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    Article
  20. 20

    INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM by Muhammad Hasbollah, Hassan

    Published 2023
    “…First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. …”
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    Thesis