Search Results - (( developing local function algorithm ) OR ( java application optimized algorithm ))

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  1. 1

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…Key features include the SMAC Hybrid A* algorithm for global path planning, the Regulated Pure Pursuit Controller for local trajectory execution and dynamic obstacle avoidance, and gmapping for SLAM functionality. …”
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    Final Year Project / Dissertation / Thesis
  2. 2

    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…A Genetic Algorithm forms the core scheduling engine, generating optimized timetables that respect both hard constraints, such as avoiding clashes, and soft constraints, such as personal preferences.The final output of this project is a functional web-based timetable planner that successfully enhances scheduling efficiency, reduces the likelihood of errors, and improves the overall academic planning experience. …”
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    Final Year Project / Dissertation / Thesis
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    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
  5. 5

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    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
    “…At the initial stage, an auxiliary function is introduced in discrete filled function method which turns the local minimizer of the original function to be a local maximizer. …”
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    Monograph
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    Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The SMA is a newly developed metaheuristic algorithm that is inspired by the slime moulds natural oscillation mode. …”
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    Conference or Workshop Item
  12. 12

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis
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    Hybrid artificial immune system-genetic algorithm optimization based on mathematical test functions by Ali M.O., Koh S.P., Chong K.H., Yap D.F.W.

    Published 2023
    “…The hybrid includes two processes; firstly, AIS is the attraction among the researchers as the algorithm. This enables it to develop local searching ability and efficiency yet the convergence rate for AIS is preferably not precise compared to the GA. …”
    Conference paper
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    Modified multi verse optimizer for solving optimization problems using benchmark functions by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2020
    “…Firstly, an average position selection mechanism is proposed for solving the local optima problem and secondly, the MVO algorithm is hybrid with another metaheuristics algorithm namely the Sine Cosine Algorithm (SCA) for better balancing the exploration and exploitation of standard MVO algorithm so that it can improve its searching capability. …”
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    Conference or Workshop Item
  16. 16

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Thesis
  17. 17

    Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function by Mohamed, Najihah

    Published 2019
    “…The optimisation technique consists of exact algorithm, and approximate algorithm. The approximate algorithm is a good technique to be highlighted since it is a feasible way to develop an easier, more convenient curve fitting method, that will save great computation, solve a large scale problem and produce a better quality end result. …”
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    Thesis
  18. 18

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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    Conference or Workshop Item
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    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Thesis
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    Detecting Remote-To-Local (R2L) attack using Decision Tree algorithm / Ahmad Nasreen Aqmal Mohd Nordin by Mohd Nordin, Ahmad Nasreen Aqmal

    Published 2024
    “…The project successfully achieves its predetermined objectives, culminating in the development of an effective Remote to Local (R2L) Intrusion Detection System utilizing the Decision Tree algorithm. …”
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    Thesis