Search Results - (( evolution optimization problem algorithm ) OR ( based optimisation swarm algorithm ))

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  1. 1

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

    Published 2016
    “…The algorithm is a hybrid algorithm that operates using dual level search strategy that takes merits of a particle swarm optimisation algorithm and a modified adaptive bats sonar algorithm. …”
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    Thesis
  2. 2

    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
  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
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    An improved particle swarm optimization algorithm for data classification by Waqas Haider Bangyal, Kashif Nisar, Tariq Rahim Soomro, Ag Asri Ag Ibrahim, Ghulam Ali Mallah, Nafees Ul Hassan, Najeeb Ur Rehman

    Published 2023
    “…Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real world. …”
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    Article
  8. 8

    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
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    Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

    Published 2023
    “…Lastly, the effectiveness of WOA and WOA-AIS in attaining optimal solutions was validated with other well-known optimisation algorithms, including particle swarm optimisation (PSO) and firefly algorithm (FA). …”
    text::Thesis
  12. 12

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

    Published 2019
    “…Nowadays, many optimisation algorithms have been introduced due to the advancement of technology such as Teaching Learning Based Optimisation (TLBO), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO) and the Bees Algorithm. …”
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    Article
  13. 13

    Metaheuristic algorithms applied in ANN salinity modelling by Khudhair, Zahraa S., Zubaidi, Salah L., Dulaimi, Anmar, Al-Bugharbee, Hussein, Muhsen, Yousif Raad, Putra Jaya, Ramadhansyah, Mohammed Ridha, Hussein, Raza, Syed Fawad, Ethaib, Saleem

    Published 2024
    “…The CPSOCGSA performance was evaluated by various single-based ones, including multi-verse optimiser (MVO), marine predator's optimisation algorithm (MPA), particle swarm optimiser (PSO), and the slim mould algorithm (SMA). …”
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    Article
  14. 14

    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
  15. 15

    A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

    Published 2011
    “…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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    Conference or Workshop Item
  16. 16

    Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation by Illias, Hazlee Azil, Wee, Zhao Liang

    Published 2018
    “…Dissolved Gas Analysis (DGA) technique is commonly used to identify oil-filled power transformer fault type but utilisation of artificial intelligence method with optimisation methods has shown convincing results. In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type. …”
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    Article
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    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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    Article
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    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
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    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses by Tarajo, Buba Ahmed, Lee, Lai Soon

    Published 2019
    “…This paper proposes a hybrid differential evolution with particle swarm optimization (DE-PSO) algorithm to solve the UTNDP, aiming to simultaneously optimize route configuration and service frequency with specific objectives in minimizing both the passengers’ and operators’ costs. …”
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    Article