Search Results - (( global optimization method algorithm ) OR ( sequence optimisation based algorithm ))

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  1. 1
    An improved particle swarm optimization algorithm for data classification

    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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  2. 2
    Hybrid optimisation electromagnetic interference shielding effectiveness:mechanical and physical performance of plaster mortar containing palm oil fuel ash using taguchi grey and taguchi-flower pollination algorithm methods

    Hybrid optimisation electromagnetic interference shielding effectiveness:mechanical and physical performance of plaster mortar containing palm oil fuel ash using taguchi grey and t... by Oh Lai Ching, Narong

    Published 2019
    “…Pre-experiment data is optimized based on Taguchi-grey and Flower Pollination Algorithm (FPA) methods. …”
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  3. 3
    Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm

    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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  4. 4
    Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation

    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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  5. 5
    An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite

    An elitist-flower pollination-based strategy for constructing sequence and sequence-less t-way test suite by Abdullah, Nasser, Kamal Z., Zamli, Alsewari, Abdulrahman A., Ahmed, Bestoun S.

    Published 2018
    “…If t-way strategies are to be adopted in such a system, there is also a need to support test data generation based on sequence of interactions. In line with such a need, this paper presents a unified strategy based on the new meta-heuristic algorithm, called the elitist flower pollination algorithm (eFPA), for sequence and sequence-less coverage. …”
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  6. 6
    Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design

    Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

    Published 2014
    “…In literature, ACS has been employed to solve DNA sequence design problem. The DNA sequence design problem was modelled based on a finite state machine in which the nodes represent the DNA bases {A, C, T, G}. …”
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  7. 7
    Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun

    Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…Particle Swarm Optimisation (PSO) was selected as the base algorithm that needs improvement and integration with other techniques. …”
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  8. 8
    Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam

    Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

    Published 2023
    “…Consequently, seeking managing of reservoir optimisation operations had always been at the forefront and to improve managing, algorithms have had been presented over the past few decades, beginning with conventional algorithms, followed by heuristic algorithms, and finally, the meta-heuristic algorithms (MHAs). …”
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  9. 9
    Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun

    Linear-pso with binary search algorithm for DNA motif discovery / Hazaruddin Harun by Harun, Hazaruddin

    Published 2015
    “…Particle Swarm Optimisation (PSG) was selected as the base algorithm that needs improvement and integration with other techniques. …”
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  10. 10
    A Study of the Contribution of Nearest-Neighbour Thermodynamic Parameters to the DNA Sequences Generated by Ant Colony Optimisation

    A Study of the Contribution of Nearest-Neighbour Thermodynamic Parameters to the DNA Sequences Generated by Ant Colony Optimisation by Mohd Zaidi, Mohd Tumari, Zuwairie, Ibrahim, Kamarul Hawari, Ghazali, Faradila, Naim, Mohd Falfazli, Mat Jusof, Ismail, Ibrahim, Zulkifli, Md. Yusof, Kamal, Khalil, Muhammad Arif, Abdul Rahim, Sophan Wahyudi, Nawawi

    Published 2013
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  11. 11
    A Hybrid Method Based on Cuckoo Search Algorithm for Global Optimization Problems

    A Hybrid Method Based on Cuckoo Search Algorithm for Global Optimization Problems by Shehab, Mohammad, Khader, Ahamad Tajudin, Laouchedi, Makhlouf

    Published 2018
    “…However, it undergoes the premature convergence problem for high dimensional problems because the algorithm converges rapidly. Therefore, we proposed a robust approach to solve this issue by hybridizing optimization algorithm, which is a combination of Cuckoo search algorithm and Hill climbing called CSAHC discovers many local optimum traps by using local and global searches, although the local search method is trapped at the local minimum point. …”
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  12. 12
    Global gbest guided-artificial bee colony algorithm for numerical function optimization

    Global gbest guided-artificial bee colony algorithm for numerical function optimization by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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  13. 13
    A Comparison of Particle Swarm optimization and Global African Buffalo Optimization

    A Comparison of Particle Swarm optimization and Global African Buffalo Optimization by Adam Kunna Azrag, Mohammed, Tuty Asmawaty, Abdul Kadir, Noorlin, Mohd Ali

    Published 2020
    “…However, in this paper, a comparison between Particle Swarm Optimization (PSO) and Global African Buffalo Optimization (GABO) algorithms was performed. …”
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  14. 14
    Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems

    Hybridizing Invasive Weed Optimization with Firefly Algorithm for Unconstrained and Constrained Optimization Problems by Hyreil A., Kasdirin, N. M., Yahya, M. S. M., Aras, Tokhi, M. O.

    Published 2017
    “…This study presents a hybrid invasive weed firefly optimization (HIWFO) algorithm for global optimization problems. …”
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  15. 15
    Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis

    Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis by Jamian, J.J., Abdullah, M.N., Mokhlis, Hazlie, Mustafa, M.W., Bakar, Ab Halim Abu

    Published 2014
    “…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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  16. 16
    A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408)

    A Novel Discrete Filled Function Algorithm in Solving Discrete Optimization Problems (S/O: 12408) by Woon, Siew Fang, Karim, Sharmila, Mohamad, Mohd Saiful Adli

    Published 2016
    “…Several global methods have been proposed for solving discrete optimization problems. …”
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  17. 17
    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost

    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

    Published 2024
    “…In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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  18. 18
    An efficient method for determining all the extreme points of function with one variable

    An efficient method for determining all the extreme points of function with one variable by Pandiya, Ridwan

    Published 2014
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  19. 19
    Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications

    Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications by Hannan M.A., Faisal M., Jern Ker P., Begum R.A., Dong Z.Y., Zhang C.

    Published 2023
    “…Carbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectiveness…”
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  20. 20
    Global optimization method for continuous - Time sensor scheduling

    Global optimization method for continuous - Time sensor scheduling by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan C.

    Published 2010
    “…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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