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  1. 1
    Improving Class Timetabling using Genetic Algorithm

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…Badly designed timetables are not just inconvenient but proved expensive in terms of wasting time and money. Hence, the major aim of this research is to investigate the internal mechanism of genetic algorithm in solving and improving class timetabling problem. …”
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  2. 2
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  3. 3
    Performance evaluation of real-time multiprocessor scheduling algorithms

    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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  4. 4
    Route Optimization System

    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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  5. 5
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
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  6. 6
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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  7. 7
    A greedy heuristics multiple criteria model for solving multi-landfill site selection and plant propagation algorithm for improving waste collection vehicle routing solutions

    A greedy heuristics multiple criteria model for solving multi-landfill site selection and plant propagation algorithm for improving waste collection vehicle routing solutions by Nur Azriati, Mat

    Published 2023
    “…First, previous models focused only on a single landfill site based on the highest score without considering the operational costs criterion in solving LSSP. Second, the Plant Propagation Algorithm (PPA) has never been considered to solve WCVRP. …”
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  8. 8
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
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  9. 9
    Faculty timetabling using genetic algorithm

    Faculty timetabling using genetic algorithm by Liong, Boon Yaun

    Published 2011
    “…Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs to solve the clashing manually.This will waste time and it is a problem for staff to solve the clashing.By implement GA,clashing will be reduced.The objective of the project is to develop aprototype in scheduling application for generates an optimum timetable for a faculty.Genetic algorithm will be implemented.The scope of FTGA is Faculty of Computer Systems & Software Engineering (FCSSE).The methodology use in this project is prototype model.The testing result show 95 out of 100 test cases achieved the maximum fitness value which means there is no clashing in the timetable.The maximum generation is set to 15 generation.Population for each generation is 3 populations.Percentage of FTGA solve the problem is 95%.…”
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    Undergraduates Project Papers
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  10. 10
    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem

    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

    Published 2008
    “…New algorithms, journal papers and computerized system were also developed. …”
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  11. 11
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
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  12. 12
    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT

    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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  13. 13
    Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite

    Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite by Suali, Anjila J., Nuraminah Ramli, Rozmie Razif Othman, Hasneeza Liza Zakaria, Iszaidy Ismail, Nor Shahida Mohd Jamail, Rimuljo Hendradi, Nurol Husna Che Rose

    Published 2025
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  14. 14
    Examination timetabling using genetic algorithm case study: KUiTTHO

    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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  15. 15
    Development of a fuzzy multi-objective mathematical model for hazardous waste location-routing problem

    Development of a fuzzy multi-objective mathematical model for hazardous waste location-routing problem by Hassani, Omid Boyer

    Published 2014
    “…In this research, a fuzzy multi-objective mixed integer programming location–routing model for the hazardous waste is developed. This study considers uncertainty in generated hazardous waste quantity by using fuzzy parametric programming. …”
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  16. 16
    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO

    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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  17. 17
    Development of novel algorithm features in the modelling of cyclic processes

    Development of novel algorithm features in the modelling of cyclic processes by Choong, Thomas S.Y., Paterson, William R., Scott, David M.

    Published 2002
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  18. 18
    DEVELOPMENT OF INTELLIGENT CONTROLLER FOR TRAFFIC LIGHTS WITH DYNAMIC PHASE ARRANGEMENT FOR SINGLE-ISOLATED INTERSECTIONS

    DEVELOPMENT OF INTELLIGENT CONTROLLER FOR TRAFFIC LIGHTS WITH DYNAMIC PHASE ARRANGEMENT FOR SINGLE-ISOLATED INTERSECTIONS by KAMAL ABBAS, MAYTHEM AL-ADILI

    Published 2014
    “…In order to solve this problem, an integrated system has been developed for managing a single intersection's traffic lights with high stability at all levels of demand. …”
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  19. 19
    Resource management in grid computing using ant colony optimization

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
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  20. 20
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
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