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  1. 1
    A discrete event simulation framework for utility accrual scheduling algorithm in uniprocessor environment

    A discrete event simulation framework for utility accrual scheduling algorithm in uniprocessor environment by Ahmad, Idawaty, K. Subramaniam, Shamala, Othman, Mohamed, Ahmad Zukarnain, Zuriati

    Published 2011
    “…GUS is one of the existing TUF/UA scheduling algorithms that consider the Time/Utility Function (TUF) of the executed tasks in its scheduling decision. …”
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  2. 2
    Sports tournament scheduling using genetic algorithm / Hafeezur Syakir Abdul Motok@Mohd Ridzuan

    Sports tournament scheduling using genetic algorithm / Hafeezur Syakir Abdul Motok@Mohd Ridzuan by Abdul Motok@Mohd Ridzuan, Hafeezur Syakir

    Published 2020
    “…The system uses the Rapid Application Development (RAD) methodology in system development and will be operate on a web-based platform. …”
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  3. 3
    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS

    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS by MEHMOOD SHAH, SYED NASIR

    Published 2012
    “…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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  4. 4
    Enhancement of Ant System Algorithm for Course Timetabling Problem

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
    “…This research starts with developing an algorithm based on original concept of Ant System Algorithm. …”
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  5. 5
    A Toolkit for Simulation of Desktop Grid Environment

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…The selected methodology for the application development is based on prototyping methodology. …”
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    Final Year Project
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  6. 6
    Adaptive resource allocation algorithms with QoS support based on network conditions using fuzzy logic system for IEEE 802.11n networks / Bakeel Hussein Naji Maqhat

    Adaptive resource allocation algorithms with QoS support based on network conditions using fuzzy logic system for IEEE 802.11n networks / Bakeel Hussein Naji Maqhat

    Published 2017
    “…The second contribution is an efficient bandwidth allocation algorithm for A-MSDU aggregation called Adaptive Scheduling based Embedded Fuzzy (ASEF) system. …”
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  7. 7
    Adaptive resource allocation algorithms with QoS support based on network conditions using fuzzy logic system for IEEE 802.11n networks / Bakeel Hussein Naji Maqhat

    Adaptive resource allocation algorithms with QoS support based on network conditions using fuzzy logic system for IEEE 802.11n networks / Bakeel Hussein Naji Maqhat by Naji Maqhat, Bakeel Hussein

    Published 2016
    “…The second contribution is an efficient bandwidth allocation algorithm for A-MSDU aggregation called Adaptive Scheduling based Embedded Fuzzy (ASEF) system. …”
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  8. 8
    Development of an integrated scheduling model for handling equipment in automated port container terminals

    Development of an integrated scheduling model for handling equipment in automated port container terminals by Sadeghian, Syed Hamidreza

    Published 2014
    “…As the integrated scheduling of handling equipment is a “non-deterministic polynomialtime hard” (NP-hard) problem and also the computation time and ease of application are so important for real practices of the scheduling methods, So a meta-heuristic algorithm based on Genetic Algorithm is developed, in which, new operators create solutions considering the constraints of the problem and also a heuristic rule proposed which assigns the ALVs to the tasks. …”
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  9. 9
    Locust- inspired meta-heuristic algorithm for optimising cloud computing performance

    Locust- inspired meta-heuristic algorithm for optimising cloud computing performance by Fadhil, Mohammed Alaa

    Published 2023
    “…This algorithm can also be used for task scheduling. The proposed algorithm efficiently maps and achieves the objective function for server consolidation, optimising energy consumption, VM migrations, and server utilisation. …”
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  10. 10
    Clonal selection algorithm for the cryptanalysis of a simple substitution cipher

    Clonal selection algorithm for the cryptanalysis of a simple substitution cipher by Ahmad, Badrisham, Maarof, Mohd. Aizaini, Ibrahim, Subariah, Kutty Mammi, Hazinah, Mohamed Amin, Muhalim, Z'aba, Muhammad Reza

    Published 2006
    “…CSA has been used in several applications such as optimization of dynamic functions and scheduling problem. …”
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  11. 11
    Modelling and optimization of a transit services with feeder bus and rail system / Mohammadhadi Almasi

    Modelling and optimization of a transit services with feeder bus and rail system / Mohammadhadi Almasi by Mohammadhadi, Almasi

    Published 2015
    “…In this study, optimized transit services and coordinated schedules are developed using metaheuristic algorithms such as genetic algorithm (GA), particle swarm optimization (PSO), water cycle algorithm (WCA) and imperialist competitive algorithm (ICA). …”
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  12. 12
    A critical analysis of simulators in grid

    A critical analysis of simulators in grid by Dakkak, Omar, Che Mohamed Arif, Ahmad Suki, Awang Nor, Shahrudin

    Published 2015
    “…Out of this, the developers have spent remarkable efforts to come up with simulators which facilitate the studies in this domain.In addition, these simulators have a significant role in enhancing and proposing many scheduling algorithms, and this in turn has reflected efficiently on the Grid.In this paper, we will present some of these tools, which are: GridSim for large scales distributed computing and parallel environment, Alea for tackling dynamic scheduling problems, Sim-G-Batch grid simulator for simulating the security and energy concept and Balls simulator for evaluation peer-to-peer with integrated load balancing algorithm.Furthermore, this paper aims to guide and assist the researcher to choose the proper tool that can fit the studied research area, by providing functionality analysis for the reviewed simulators.…”
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  13. 13
    Optimization in driver’s scheduling for university shuttle bus using harmony search

    Optimization in driver’s scheduling for university shuttle bus using harmony search by Shaffiei, Zatul Alwani, Abal Abas, Zuraida, Abdul Rahman, Ahmad Fadzli Nizam, Shibghatullah, Abdul Samad, Hussin, Burairah

    Published 2014
    “…The proposed technique is Harmony Search, which is a recently developed population-based meta heuristic optimization algorithm. …”
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  14. 14
    State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm

    State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm by Lipu M.S.H., Ayob A., Saad M.H.M., Hussain A., Hannan M.A., Faisal M.

    Published 2023
    Conference Paper
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  15. 15
    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan Yin Keong, Tan Yin

    Published 2012
    “…A technique for obtaining globally optimal schedules for the flow of crude is developed. A continuous time model based on transfer events is used to represent the scheduling problem and this model is a nonconvex MINLP model which presents multiple local optima. …”
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    Final Year Project
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  16. 16
    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan , Yin Keong

    Published 2009
    “…A technique for obtaining globally optimal schedules for the flow of crude is developed. Acontinuous time model based on transfer events is used to represent the scheduling problem and this model is a nonconvex MINLP model which presents multiple local optima. …”
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    Final Year Project
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  17. 17
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  18. 18
    Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System

    Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System by Arab, Ali

    Published 2009
    “…The results in the simulated testbed indicate that the developed scheduling method using simulation optimization functions properly and can be applied in other cases.…”
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  19. 19
    Smart Routing For Solid Waste Collection

    Smart Routing For Solid Waste Collection by Ngiam, John Tze

    Published 2023
    “…Testing is conducted to validate the functionality and performance of the system. Finally, the conclusion highlights the accomplishments of the project, including the successful development of the route optimization algorithm and the web-based application. …”
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    Final Year Project Report / IMRAD
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  20. 20
    Smart student timetable planner

    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…Course data is managed in CSV format, parsed into JSON for fast processing, while sessionStorage and localStorage handle user data within active sessions. 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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