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  1. 1
    Improving resource management with multi-instance broker scheduling algorithm in hierarchical grid computing

    Improving resource management with multi-instance broker scheduling algorithm in hierarchical grid computing by Yahaya, Bakri

    Published 2016
    “…Multi-Instance Broker Scheduling Algorithm (MiBSA) has been proposed as a new scheduling algorithm to get rid of the drawback from the iHLBA algorithm. …”
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  2. 2
    A Toolkit for Simulation of Desktop Grid Environment

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

    Published 2014
    “…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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  3. 3
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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  4. 4
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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  5. 5
    Parallel metaheuristic algorithm for route planning using CUDA

    Parallel metaheuristic algorithm for route planning using CUDA by Looi, Daniel Jun Jie

    Published 2025
    “…Area of Study: Massively Parallel Computing, Combinatorial Optimization Keywords: Parallel Metaheuristic Algorithm, Travelling Salesman Problem, CUDA, GPU, Genetic Algorithm…”
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  6. 6
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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  7. 7
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  8. 8
    A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU)

    A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU) by Mohd Johar, Fauzi, Azmin, Farah Ayuni, Suaidi, Mohd Kadim, Shibghatullah, Abdul Samad, Ahmad, Badrul Hisham, Salleh, Siti Nadzirah, Abdul Aziz, Mohd Zainol Abidin, Md Shukor, Mahfuzah

    Published 2013
    “…Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. …”
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  9. 9
    SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment

    SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment by Murad, Saydul Akbar, Zafril Rizal, M. Azmi, Muzahid, Abu Jafar Md, Bhuiyan, Md Khairul Bashar, Saib, Md, Rahimi, Nick, Prottasha, Nusrat Jahan, Bairagi, Anupam Kumar

    Published 2024
    “…To address this issue, the main objective of this research is to improve the existing Priority Rules (PR) cloud schedulers by developing a new dynamic scheduling algorithm by manipulating the gaps in the cloud job schedule. …”
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  10. 10
    A GPGPU Approach to Accelerate Ant Swarm Optimization Rough Reducts (ASORR) Algorithm

    A GPGPU Approach to Accelerate Ant Swarm Optimization Rough Reducts (ASORR) Algorithm by Udayanti, Erika Devi, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah, Nugroho, Fajar Agung

    Published 2012
    “…In order to find a reducts, a such applications of rough set uses a discernibility matrix. Ant Swarm Optimization Rough Reducts (ASORR) algorithm is used in rough reducts calculation for identifying significant attribute set optimally. …”
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  11. 11
    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes

    Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes by Mohammad Sigit Arifianto, Tze, Kenneth Kin Teo, Liau, Chung Fan, Liawas Barukang, Zaturrawiah Ali Omar

    Published 2007
    “…They have to be optimized for parallel execution while some parts still do have sequential execution due to data dependencies, which makes the optimization problem two folds, parallel and serial. …”
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  12. 12
    A parallel prevention algorithm for black hole attacks in MANET

    A parallel prevention algorithm for black hole attacks in MANET by Yaakub, Abdul Razak, Ghathwan, Khalil I.

    Published 2015
    “…In this paper, we propose a parallel algorithm for MANETs that optimizes both routing discovery and security in an Ad Hoc On Demand Distance Vector (AODV). …”
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  13. 13
    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms

    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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  14. 14
    Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad

    Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad by Saima Gulzar, Ahmad

    Published 2017
    “…Similarly, when data parallelism is introduced in the algorithm the performance of the algorithm improved further by 12% in latency and 17% in throughput when compared to PDWA algorithm. …”
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  15. 15
    Smart student timetable planner

    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…The objectives of this project are to generate conflict-free and customizable schedules, enable real-time collaboration among students, and offer administrative tools for maintaining course information. …”
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  16. 16
    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil

    Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil by Ahmad, Ahmad Firdaus

    Published 2014
    “…Evolutionary computation (EC) is a method that is ubiquitously used to solve complex computation. Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. …”
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  17. 17
    Classroom finder system with student availability, space and time constraint

    Classroom finder system with student availability, space and time constraint by Loh, Yong Bin

    Published 2024
    “…The primary focus of the system is on facilitating efficient and conflict-free room assignments while considering various constraints and requirements by exploring the suitable Artificial Intelligence approaches and scheduling algorithms. Therefore, the project scopes are to identify the specific constraints and requirements to be considered in the Classroom Finder System and also explore the suitable Artificial Intelligence approaches and room allocation and scheduling algorithms. …”
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  18. 18
    PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems

    PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems by Mushtaq, Najeeb, Ramdan, Razali, K. G., Mohammed, Hamdan, Daniyal, Ali, M. Humada

    Published 2016
    “…In this research, the automatic generation control (AGC) of three parallel-connected power plants is utilized to tune the proportional-integral-derivative (PID) controller using Multistart algorithm (MS). …”
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  19. 19
    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design

    Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design by Haohao, Ma, As’arry, Azizan, Yanwei, Feng, Lulu, Cheng, Delgoshaei, Aidin, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi

    Published 2024
    “…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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  20. 20
    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
    “…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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