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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
    “…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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    Thesis
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  2. 2
    Automated time series forecasting

    Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

    Published 2011
    “…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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    Monograph
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  3. 3
    Text messaging encryption system

    Text messaging encryption system by Sundara Morthty, Nirmala Devi

    Published 2012
    “…Currently messages in phone can easily be read if the phone is stolen,or users might simply send it to the wrong number.Messages need to be encrypted to solve this problem. With this only the sender and recipient will be able to send and receive private information. …”
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    Undergraduates Project Papers
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  4. 4
    Development of mobile application of event assistant and booking sport facilities for UiTM Seremban 3 Campus using wofkflow management system / Ahmad Haiqal Abd Halim, Ahmad Yusuf Che Hassan and Mohd Norhafizi Hambari

    Development of mobile application of event assistant and booking sport facilities for UiTM Seremban 3 Campus using wofkflow management system / Ahmad Haiqal Abd Halim, Ahmad Yusuf... by Abd Halim, Ahmad Haiqal, Che Hassan, Ahmad Yusuf, Hambari, Mohd Norhafizi

    Published 2019
    “…In this research, its content of the step on how to apply the method of WfMS in a mobile application with the use of an android studio. The algorithm for the WfMS is written using Java script in this research. …”
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  5. 5
    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem

    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem by Fayaz, Muhammad, Arshad,, Shakeel, Shah,, Abdul Salam, Shah, Asadullah

    Published 2018
    “…Background and Objective: The process of solving the Maximum Clique (MC) problem through approximation algorithms is harder, however, the Maximum Vertex Cover (MVC) problem can easily be solved using approximation algorithms. …”
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  6. 6
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…Optimization is an important process in solving most engineering problems. Unfortunately, many practical optimization problems cannot be solved to optimality within reasonable computational effort. …”
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  7. 7
    Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources

    Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources by Abed, Munther Hameed, Mohd Nizam Mohmad, Kahar

    Published 2022
    “…Here, we proposed genetic algorithm (GA) to solve the UPMR problem because of the robustness and the success of GA in solving many optimization problems. …”
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  8. 8
    Generic DNA encoding design scheme to solve combinatorial problems

    Generic DNA encoding design scheme to solve combinatorial problems by Rofilde, Hasudungan

    Published 2015
    “…The complexity of combinatorial problems is classified as NP meaning that algorithms are yet to exist to efficiently solve the problem. …”
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  9. 9
    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources

    Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources by Abed, Munther H., Mohd Nizam, Mohmad Kahar

    Published 2023
    “…Genetic algorithm shows promising results in solving UPMR. …”
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  10. 10
    Implication of image processing algorithm in remote sensing and GIS applications

    Implication of image processing algorithm in remote sensing and GIS applications by Pathan, Mubeena, Jusoff, Kamaruzaman, Mohd Sood, Alias, Razali, Yaakob, Qureshi, Barkatullah

    Published 2011
    “…An algorithm solves the complex problems more efficiently and consistently. …”
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  11. 11
    An improved sine cosine algorithm for solving optimization problems

    An improved sine cosine algorithm for solving optimization problems by Mohd Helmi, Suid, Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Addie Irawan, Hashim, Raja Mohd Taufika, Raja Ismail, Mohd Zaidi, Mohd Tumari

    Published 2018
    “…Due to its simplicity and less tedious parameter tuning over other multi-agent-based optimization algorithms, Sine Cosine Algorithm (SCA) has gained lots of attention from numerous researchers for solving optimization problem. …”
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  12. 12
    Levy slime mould algorithm for solving numerical and engineering optimization problems

    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 proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
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  13. 13
    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems

    Levy tunicate swarm algorithm for solving numerical and real-world optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The proposed Levy Tunicate Swarm Algorithm (LTSA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic algorithm called Tunicate Swarm Algorithm (TSA) to solve numerical and real-world optimization problems. …”
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  14. 14
    The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement

    The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

    Published 2025
    “…SGA is used in the process of solving optimization test problems by neural networks. …”
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  15. 15
    Optimization of mycelium growth using genetic algorithm for multi-objective functions

    Optimization of mycelium growth using genetic algorithm for multi-objective functions by Muhamad Faiz, Abu Bakar

    Published 2019
    “…Trade-off between the objectives, exist for the optimization process. To solve this issues, multi-objective genetic algorithm was chosen as the methodology for this project, specifically using NSGA-ii algorithm. …”
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  16. 16
    Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid

    Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid by Wahid, Juliana

    Published 2017
    “…SA is chosen to be hybridize with HSA for solving CBCTT because in literature, SA was successfully hybridize with HSA to solve other domain of problems. …”
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  17. 17
    Ant colony optimization in dynamic environments

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…This thesis is an investigation into the application ' of ACO for solving dynamic optimization problems. The first objective of this study is to identify which ant algorithm performs the best under a dynamic environment. …”
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  18. 18
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Optimization problems are frequently found in various fields. The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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  19. 19
    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…A two-step enhanced non-dominated sorting HHMO (2SENDSHHMO) algorithm has been proposed to solve this problem. …”
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  20. 20
    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri

    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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