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  1. 1
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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    Thesis
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  2. 2
    Visdom: Smart guide robot for visually impaired people

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

    Published 2025
    “…The system architecture integrates ROS 2 on a Raspberry Pi, with TCP/IP connectivity enabling remote operation. An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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  3. 3
    Block matching algorithms for motion estimation using modified Cross-Diamond-Hexagonal search / Abd Razak Mahmud

    Block matching algorithms for motion estimation using modified Cross-Diamond-Hexagonal search / Abd Razak Mahmud by Mahmud, Abd Razak

    Published 2008
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  4. 4
    Very Large Scale Integration Cell Based Path Extractor For Physical To Layout Mapping In Fault Isolation Work

    Very Large Scale Integration Cell Based Path Extractor For Physical To Layout Mapping In Fault Isolation Work by Pragasam, Matthew

    Published 2017
    “…To be able to retrieve all possible signals involved within a suspected boundary is a popular search computational problem. Therefore the path extractor program proposed incorporates the characteristics of a depth-first search algorithm by considering the specifications of a cell-based design. …”
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  5. 5
    Global optimal analysis of variant genetic operations in solar tracking

    Global optimal analysis of variant genetic operations in solar tracking by Fam D.F., Koh S.P., Tiong S.K., Chong K.H.

    Published 2023
    “…Genetic Algorithms (GAs), Evolution Strategies (ES), Evolutionary Programming (EP) and Genetic Programming (GP) are some of the best known types of Evolutionary Algorithm (EA)where it is a class of global search algorithms inspired by natural evolution. …”
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  6. 6
    Box-jenkins and genetic algorithm hybrid model for electricity forecasting system

    Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

    Published 2005
    “…By adopting the GA blind search, the algorithm combines searching techniques and their capabilities to learn about the relationship of the pattern-recognition of the past data. …”
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  7. 7
    Problem restructuring in interger programming for reduct searching

    Problem restructuring in interger programming for reduct searching by Ungku Chulan, Ungku Azmi Iskandar

    Published 2003
    “…Standard Integer Programming / Decision Related Integer Programming (SIP/DRIP) is a reduct searching system that finds the reducts in an information system. …”
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  8. 8
    Breaking A Playfair Cipher Using Single and Multipoints Crossover Based on Heuristic Algorithms

    Breaking A Playfair Cipher Using Single and Multipoints Crossover Based on Heuristic Algorithms by Naji M.A., Atee H.A., Jebur R.S., Hammood D.A., Der C.S., Abosinnee A.S., Yasari A.K.I., Ahmad R.B.

    Published 2023
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  9. 9
    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems

    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…This thesis studies multiobjective UTSP consisting of frequency setting, timetabling, simultaneous bus and driver scheduling by applying Multiple Tabu Search (MTS) algorithm. Metaheuristic methods have been widely applied to solve UTSP which is a NP-hard problem. …”
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  10. 10
    Online food ordering application using Boyer-Moore algorithm / Muhammad Zulhilmie Dzulkifli

    Online food ordering application using Boyer-Moore algorithm / Muhammad Zulhilmie Dzulkifli by Dzulkifli, Muhammad Zulhilmie

    Published 2021
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  11. 11
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…In recent years, extensive works on genetic algorithms have been reported covering various applications. …”
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  12. 12
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…In recent years, extensive works on genetic algorithms have been reported covering various applications. …”
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  13. 13
    Model structure selection for a discrete-time non-linear system using genetic algorithm

    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…In recent years, extensive works on genetic algorithms have been reported covering various applications. …”
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  14. 14
    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes

    Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes by Nor Atiqah, Zolpakar, Lodhi, Swati Singh, Pathak, Sunil, Sharma, Mohita Anand

    Published 2020
    “…Multi-objectives Genetic Algorithm (MOGA) is one of many engineering optimization techniques, a guided random search method. …”
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  15. 15
    An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.

    An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications. by S. Ahmed, Bestoun, Enoiu, Eduard, Afzal, Wasif, Kamal Z., Zamli

    Published 2020
    “…Hyper-heuristic is a new methodology for the adaptive hybridization of meta-heuristic algorithms to derive a general algorithm for solving optimization problems. …”
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  16. 16
    Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi

    Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi by Seyedmehdi, Mirmohammadsadeghi

    Published 2015
    “…Therefore, multi-point simulated annealing (M-SA), memetic algorithm (MA) and tabu search (TS) algorithms are applied to solve the TTRPSD. …”
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  17. 17
    Petri Net Algorithm for controlling and monitoring system

    Petri Net Algorithm for controlling and monitoring system by Mohamad Shaiful, Osman

    Published 2009
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    Working Paper
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  18. 18
    Model structure selection for a discrete-time non-linear system using a genetic algorithm

    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…In recent years, extensive works on genetic algorithms have been reported covering various applications. …”
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  19. 19
    Grey Wolf Optimizer for Solving Economic Dispatch Problems

    Grey Wolf Optimizer for Solving Economic Dispatch Problems by Wong, Lo Ing, M. H., Sulaiman, Mohd Rusllim, Mohamed, Hong, Mee Song

    Published 2014
    “…The algorithm is then benchmarked on 20 generating units in economic dispatch, and the results are verified by a comparative study with Biogeography-based optimization (BBO), Lambda Iteration method (LI), Hopfield model based approach (HM), Cuckoo Search (CS), Firefly, Artificial Bee Colony (ABC), Neural Networks training by Artificial Bee Colony (ABCNN), Quadratic Programming (QP) and General Algebraic Modeling System (GAMS). …”
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    Conference or Workshop Item
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  20. 20
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…Tests results show that Genetic Algorithm is a suitable algorithm as it is an optimization technique with, high accuracy, and it avoids local minimum by searching in several regions to arrive to the global optimum solution. …”
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