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  1. 1
    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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  2. 2
    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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  3. 3
    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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  4. 4
    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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  5. 5
    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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  6. 6
    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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    Monograph
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  7. 7
    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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    Thesis
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  8. 8
    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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  9. 9
    Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network

    Efficient Sequential and Parallel Routing Algorithms in Optical Multistage Interconnection Network by Abduh Kaid, Monir Abdullah

    Published 2005
    “…This routing problem is an NPhard problem. Many algorithms are designed by many researchers to perform this routing such as window method, sequential algorithm, degree-descending algorithm, simulated annealing algorithm, genetic algorithm and ant colony algorithm.This thesis explores two approaches, sequential and parallel approaches. …”
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  10. 10
    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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  11. 11
    Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.]

    Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.] by Abdul Majid, M. M., Salleh, M. S., Abu Hashim, M. A., Ismail, N. H., Mansor, S., Abu Bakar, S. A.

    Published 2018
    “…The publication presents a controller strategy used in development of Semi Active Lateral Control (SALC) algorithm for passenger vehicle in enhancing transient handling performance using multibody co-simulation approach. …”
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  12. 12
    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach

    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach by Najeeb, Mushtaq, Muhamad, Mansor, Ramdan, Razali, Hamdan, Daniyal, Ali, Mahmood

    Published 2017
    “…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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  13. 13
    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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  14. 14
    Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation

    Non-probabilistic approach to cooperative position tracking in large swarm of simple mobile robots using triangular cross-observation by Din, Abdul Sattar

    Published 2013
    “…The performance of the algorithm was validated and compared against that of the EKF through series of simulations using Stage multi-agent simulator. …”
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  15. 15
    Simulation algorithm of bayesian approach for choice-conjoint model

    Simulation algorithm of bayesian approach for choice-conjoint model by Zulhanif

    Published 2011
    “…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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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
    A branch and bound and simulated annealing approach for job shop scheduling

    A branch and bound and simulated annealing approach for job shop scheduling by Tan, Hui Woon, Salim, Sutinah

    Published 2004
    “…In the branch and bound approach, the job shop scheduling problem is represented by a disjunctive graph, then the optimal schedule is obtained using the branch and bound algorithm while simulated annealing is a local search based algorithm which will slightly perturb the initial feasible solution to decrease the makespan. …”
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  18. 18
    Implementation of laser simulator in robot path determination

    Implementation of laser simulator in robot path determination by Zenas, Chung Han Yuan

    Published 2016
    “…In addition, one of the classical path planning approach which is A* algorithm will be used to compare the result generated by laser simulator. …”
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    Undergraduates Project Papers
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  19. 19
    Improving Class Timetabling using Genetic Algorithm

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

    Published 2006
    “…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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  20. 20
    Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus

    Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus by Abu Bakar, Nordin, Abdul Kudus, Rosnawati

    Published 2009
    “…Learning is a complex cognitive process; thus, the algorithms that can simulate learning are also complex. …”
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