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  1. 1
    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
    “…The simulation is implemented with iFogSim and java programming language. …”
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  2. 2
    Maintenance staff scheduling system using heuristic-greedy algorithm / Nurliyana Sabli

    Maintenance staff scheduling system using heuristic-greedy algorithm / Nurliyana Sabli by Sabli, Nurliyana

    Published 2010
    “…The scheduling part will be developed using heuristic – greedy algorithm. …”
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  3. 3
    Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals

    Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals by Homayouni, Seyed Mahdi

    Published 2012
    “…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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  4. 4
    Development of priority oriented scheduling method to increase the efficiency and reliability for automotive job

    Development of priority oriented scheduling method to increase the efficiency and reliability for automotive job by Nojabaei, Seyedehfarzaneh

    Published 2012
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  5. 5
    Bus Driver Scheduling System via Genetic Algorithm with Enhanced Crossover Mechanism

    Bus Driver Scheduling System via Genetic Algorithm with Enhanced Crossover Mechanism by Lim, Tze Shung

    Published 2009
    “…Hence, the objective of the study is to develop a model to solve the bus driver scheduling problem (BDSP). …”
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  6. 6
    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
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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
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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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
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
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  9. 9
    A study of an efficient scheduling algorithm for simultaneous 5G multimedia Traffic

    A study of an efficient scheduling algorithm for simultaneous 5G multimedia Traffic by Mohd Ramli, Huda Adibah, Abdalla Hashim, Aisha Hassan, Mohamed Rasied, Thaahirah Shireen, Asnawi, Ani Liza, Abdul Rahman, Farah Diyana

    Published 2022
    “…Moreover, most 5G packet scheduling algorithms support only one multimedia use case. …”
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  10. 10
    Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids

    Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids by Abduh Kaid, Monir Abdullah

    Published 2009
    “…The first stage is to develop new DLT based models for multiple sources scheduling. …”
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  11. 11
    Managing risk in production scheduling under uncertain disruption

    Managing risk in production scheduling under uncertain disruption by Sarker, Ruhul, Essam, Daryl, Kamrul Hasan, S.M., Karim, A.N. Mustafizul

    Published 2015
    “…We have first solved JSPs using an improved memetic algorithm and extended the algorithm to deal with the disruption situations, and then developed a simulation model to analyze the risk of using a job order and delivery scenario. …”
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  12. 12
    Great Deluge and Extended Great Deluge based job scheduling in grid computing using GridSim

    Great Deluge and Extended Great Deluge based job scheduling in grid computing using GridSim by Seifaddini, Omid, Abdullah, Azizol, Muhammed, Abdullah, Hussin, Masnida

    Published 2016
    “…We also, investigate the computation time and the number of soft constraints violations of EGD against its conventional GD algorithm. The GD scheduling algorithm is able to provide qualitative solution in shorter time for small Grid size while EGD could produce schedule in shorter time for all cases.…”
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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
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  14. 14
    Penggunaan kaedah algoritma genetik dalam permasalahan penjadualan PCB: kajian kes di industri elektronik

    Penggunaan kaedah algoritma genetik dalam permasalahan penjadualan PCB: kajian kes di industri elektronik by Zalinda Othman

    Published 2010
    “…This paper proposes the use of Genetic Algorithm in solving scheduling problems and the case study has been conducted in printed circuit board assembly company. …”
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  15. 15
    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
    “…In addition, results proved that the modified meta-heuristic algorithm is able to find near optimal solutions and on average, the solutions found by the GA algorithm are only 0.2% worse than the optimal solutions and in the worst case in the test cases this difference is 2.3% which is acceptable. …”
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  16. 16
    Runtime pluggable CPU scheduler for linux operating system

    Runtime pluggable CPU scheduler for linux operating system by Al-Maweri, Nasr Addin Ahmed Salem

    Published 2010
    “…It also provides a flexible interface for kernel developers which facilitates the evaluation and testing for their newly developed scheduling algorithms. …”
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  17. 17
    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO

    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
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  18. 18
    Innovative crossover and mutation in a genetic algorithm based approach to a campus bus driver scheduling problem with break consideration and embedded overtime

    Innovative crossover and mutation in a genetic algorithm based approach to a campus bus driver scheduling problem with break consideration and embedded overtime by Ramli, Razamin, Ibrahim, Haslinda, Lim, Tze Shung

    Published 2013
    “…The unfairness of job distribution and the ineffectiveness of break-time assignment among bus drivers are factors identified as problem issues in the bus driver management in a university campus environment.The issues affect the quality of the bus service which then pointed to the efficiency or inefficiency of the bus driver scheduling system.Thus, this study investigates the problem and constraints connected to bus driver scheduling activities as a case in a campus environment.Therefore, we developed an efficient bus driver scheduling model based on the Genetic Algorithm (GA) approach. …”
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  19. 19
    Explaining recreationist responsible behaviour : a case of scuba diving / Ong Tah Fat

    Explaining recreationist responsible behaviour : a case of scuba diving / Ong Tah Fat by Ong, Tah Fat

    Published 2012
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  20. 20
    An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II

    An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II by Delgoshaei, Aidin, Mohd Ariffin, Mohd Khairol Anuar, Leman, Zulkiflle

    Published 2022
    “…Then, a fuzzy-weighted NSGA-II is proposed (FW-NSGA-II) to address the developed Non-linear Fuzzy Multi-objective Dual resource-constrained scheduling problem. …”
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