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  1. 1
    Particle swarm optimization (PSO) for CNC route problem

    Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

    Published 2002
    “…We often see many of the method of Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing Algorithm (SAA) and PSO are used for any optimization problems. …”
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    Undergraduates Project Papers
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  2. 2
    Simulation and Visualization of TSP Using Ant Colony Optimization

    Simulation and Visualization of TSP Using Ant Colony Optimization by Tri Basuki, Kurniawan, Misinem, ., Astried, ., Joan Angelina, Widians

    Published 2023
    “…This model can be used to explain how to solve the traveling salesman problem by providing step-by-step instructions performed by users using ant colony optimization. …”
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  3. 3
    A firefly algorithm based hybrid method for structural topology optimization

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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  4. 4
    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique

    SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique by Doroody C., Tiong S.K., Darzi S.

    Published 2023
    Conference Paper
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  5. 5
    PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM

    PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM by Hasdi Aimon, Arhimny

    Published 2012
    “…In this project, Particle Swarm Optimization (PSO) as one of Swarm Intelligence Algorithm based has proposed to be integrated with PID (Proportional, Integral, Derivative) Controller in order to achieve optimal tuning method. …”
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    Final Year Project
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  6. 6
    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller

    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller by Ismail, H. Muh Yusuf

    Published 2010
    “…GA have been successfully applied to solve many optimization problems. This research proposes a method that may help users to determine the membership function of FLC using the technique of GA optimization for the fastest processing in solving the problems. …”
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    Thesis
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  7. 7
    Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals

    Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals by Suhail Najm, Shahab, Ayib Rosdi, Zainun, Nurul Hazlina, Noordin, Izzeldin, I. Mohd

    Published 2018
    “…Heuristic optimization algorithms are broadly used to solve many engineering problems. …”
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  8. 8
    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS

    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS by MEHMOOD SHAH, SYED NASIR

    Published 2012
    “…The four prime aspects of this work are: firstly, a model of the grid scheduling problem for dynamic grid computing environment; secondly, development of a new web based simulator (SyedWSim), enabling the grid users to conduct a statistical analysis of grid workload traces and provides a realistic basis for experimentation in resource allocation and job scheduling algorithms on a grid; thirdly, proposal of a new grid resource allocation method of optimal computational cost using synthetic and real workload traces with respect to other allocation methods; and finally, proposal of some new job scheduling algorithms of optimal performance considering parameters like waiting time, turnaround time, response time, bounded slowdown, completion time and stretch time. …”
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  9. 9
    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam

    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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  10. 10
    HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets

    HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets by Hasan, Raed Abdulkareem, Mostafa, A. Mohammed, Salih, Zeyad Hussein, M. A., Ameedeen, Tapus, Nicolae, Mohammed, Muamer N.

    Published 2018
    “…With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). …”
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  11. 11
    Summary of best efficient algorithms on cognitive radio cooperative spectrum sensing to improve QoS

    Summary of best efficient algorithms on cognitive radio cooperative spectrum sensing to improve QoS by Akbari, M., Reza, A.W., Noordin, K.A., Manesh, M.R., Hindia, M.N.

    Published 2014
    “…In fact, all steps of genetic algorithm (GA), particle swarm optimization (PSO) and imperialistic competitive algorithm (ICA) will be well mentioned in details and investigated on cognitive radio cooperative spectrum sensing (CRCSS) method. …”
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    Conference or Workshop Item
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  12. 12
    Hybrid Henry Gas-Harris Hawks comprehensive-opposition algorithm for task scheduling in cloud computing

    Hybrid Henry Gas-Harris Hawks comprehensive-opposition algorithm for task scheduling in cloud computing by Omran Alkaam, Nora, Md Sultan, Abu Bakar, Hussin, Masnida, Yatim Sharif, Khaironi

    Published 2025
    “…This method is based on two elements: comprehensive opposition-based learning (COBL) and Harris Hawks Optimization (HHO). …”
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  13. 13
    Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman

    Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

    Published 2025
    “…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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    Thesis
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  14. 14
    Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks

    Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks by Hussein, Yassein Soubhi

    Published 2014
    “…The results demonstrated that our proposed method results in significant reductions of HOF, HOPP and packet loss ratio (PLR) compared to the conventional HHO and enhanced weighted performance HO parameter optimization (EWPHPO) algorithm. …”
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  15. 15
    Resource allocation in coordinated multipoint long term evolution-advanced networks

    Resource allocation in coordinated multipoint long term evolution-advanced networks by Katiran, Norshidah

    Published 2015
    “…ORA is formulated based on Lagrangian method and optimized using Particle Swarm Optimization (PSO). …”
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  16. 16
    Optimal sizing and location of distributed generation for loss minimization using firefly algorithm

    Optimal sizing and location of distributed generation for loss minimization using firefly algorithm by Bin Kamarudin M.N., Hashim T.J.T., Musa A.

    Published 2023
    “…As the incorporation of DG in the power distribution network creates several problems to the network operators, locating a suitable capacity and placement for DG will essentially help to improve the quality of power delivery to the end users. This paper presents the simulation of an application of firefly algorithm (FA) for optimally locating the most suitable placement and capacity of distributed generation (DG) in IEEE 33-bus radial distribution network. …”
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  17. 17
    Fair energy-efficient resource allocation for downlink NOMA heterogeneous networks

    Fair energy-efficient resource allocation for downlink NOMA heterogeneous networks by Ali, Zuhura Juma, Noordin, Nor Kamariah, Sali, Aduwati, Hashim, Fazirulhisyam

    Published 2020
    “…The energy consumption of both the transmitter and the receiver are considered to simulate the real system design. The Greedy Algorithm (GA) is used to achieve a low-complex optimal solution during the user-pairing process. …”
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  18. 18
    Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements

    Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements by Ramadhan, Mazen Farid Ebrahim

    Published 2022
    “…All the proposed algorithms are simulated using the popular cloud simulator, Workflowsim 1.0. …”
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  19. 19
    Tree physiology optimization on SISO and MIMO PID control tuning

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…This concept may improve the search mechanism with a better trade-off between diversification and intensification search. A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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  20. 20
    Tree physiology optimization on SISO and MIMO PID control tuning

    Tree physiology optimization on SISO and MIMO PID control tuning by Halim, A.H., Ismail, I.

    Published 2018
    “…This concept may improve the search mechanism with a better trade-off between diversification and intensification search. A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Zieglerâ��Nichols, Tyreusâ��Luyben and Chienâ��Hronesâ��Reswick methods. …”
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