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  1. 1
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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  2. 2
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…A set of modified and novel optimization algorithms are proposed in this thesis to deal with different single and multi-objective OPF problems. …”
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  3. 3
    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution

    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2018
    “…Significant modifications to the basic Jaya algorithm are done to create a modified Jaya (MJaya) algorithm that can handle the MOOPF problem. …”
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  4. 4
    Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application

    Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application by Hardhienata, Medria Kusuma Dewi, Priandana, Karlisa, Putra, Daffa Rangga, Sriatun, Mamiek, Wulandari, Buono, Agus, Mohamed, Raihani

    Published 2024
    “…The performance of the basic ACO algorithm for solving task allocation is improved by modifying the efficiency factor. …”
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  5. 5
    Data Analysis using Particle Swarm Optimization Algorithm

    Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

    Published 2015
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    Final Year Project / Dissertation / Thesis
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  6. 6
    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization

    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization by Modarres, Farzin, Abu Hassan, Malik, Leong, Wah June

    Published 2009
    “…In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. …”
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  7. 7
    Improved Multi-Verse Optimizer In Text Document Clustering For Topic Extraction

    Improved Multi-Verse Optimizer In Text Document Clustering For Topic Extraction by Abasi, Ammar Kamal Mousa

    Published 2021
    “…Second, three multi-verse optimizer algorithm (MVOs), namely, basic MVO, modified MVO, hybrid MVO is proposed to solve the TDC problem; these algorithms are incremental improvements of the preceding versions. …”
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  8. 8
    Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm

    Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm by Wang, Wei, Liu, Yao

    Published 2016
    “…In this paper, a modified Cuckoo searching algorithm is proposed to solve the multiple objective Green Logistics optimization problem. …”
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  9. 9
    Particle Swarm Optimization algorithm for facial emotion detection

    Particle Swarm Optimization algorithm for facial emotion detection by Ghandi, B.M., Nagarajan, R., Hazry, Desa, Prof. Madya Dr.

    Published 2010
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  10. 10
    Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic Algorithm

    Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic Algorithm by Abed I.A., Koh S.P., Sahari K.S.M., Jagadeesh P., Tiong S.K.

    Published 2023
    “…A method based on a modified electromagnetism-like with two-direction local search algorithm (MEMTDLS) and genetic algorithm (GA) is proposed to determine the optimal time of task scheduling for dual-robot manipulators. …”
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  11. 11
    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…Many real-world production scheduling problems involve the simultaneous optimization of multiple conflicting objectives that are challenging to solve without the aid of powerful optimization techniques. …”
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  12. 12
    T-way testing : a test case generator based on melody search algorithm

    T-way testing : a test case generator based on melody search algorithm by Toh, Shu Yuen

    Published 2015
    “…Next, TTT-MS will be executed through main algorithms to generate Parameters Interaction List, Parameter Values Interaction List, and finally generate final Test Cases based on Melody Search Algorithm. …”
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    Undergraduates Project Papers
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  13. 13
    Integration of enchanced jump point search (JPS) algorithm with modified bresenham technique for path planning in virtual grid-based environment

    Integration of enchanced jump point search (JPS) algorithm with modified bresenham technique for path planning in virtual grid-based environment by Nurul Atikah Janis

    Published 2018
    “…We demonstrate our framework; the integration of enhanced Jump Point Search algorithm with modified Bresenham for heuristic computation in virtual grid-based environment. …”
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  14. 14
    Mathematical formulation of tabu search in combinatorial optimization

    Mathematical formulation of tabu search in combinatorial optimization by Ismail, Zuhaimy

    Published 2008
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    Monograph
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  15. 15
    Power line faults classification by neural network train by Ant Colony Optimization

    Power line faults classification by neural network train by Ant Colony Optimization by Nasirudin, Mohd Syafiq

    Published 2017
    “…Metaheuristic algorithms are algorithms which, in order to escape from local optima, drive some basic heuristic: either a constructive heuristic starting from a null solution and adding elements to build a good complete one, or a local search heuristic starting from a complete solution and iteratively modifying some of its elements in order to achieve a better one. …”
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  16. 16
    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics

    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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  17. 17
    System identification using Extended Kalman Filter

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…The EKF algorithm performance was compared with Recursive Least Square (RLS) estimation algorithm as a comparison algorithm performance. …”
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  18. 18
    Facial emotion detection using Guided Particle Swarm Optimization (GPSO)

    Facial emotion detection using Guided Particle Swarm Optimization (GPSO) by Bashir, Mohammed Ghandi, Nagarajan, R., Hazry, Desa

    Published 2009
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  19. 19
    Enhancement Of Traffic Collision Avoidance Using Token Bucket Algorithm

    Enhancement Of Traffic Collision Avoidance Using Token Bucket Algorithm by Mat Nawi, Nor Afifah

    Published 2016
    “…In this project, the optimal size of bucket in Token Bucket Algorithm is used as one of the techniques in traffic shaping. …”
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  20. 20
    INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM

    INTELLIGENT OPTIMIZATION OF INTERLINE POWER FLOW CONTROLLER IN TRANSMISSION SYSTEM by MOHAMED ABDELGADIR, KHALID HAROUN

    Published 2010
    “…The optimal parameters are derived to minimize the transmission line losses using three intelligent optimization techniques, namely Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA). …”
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