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  1. 1

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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    Monograph
  2. 2

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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    Thesis
  3. 3

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
    “…Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources.Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which lead to the resources having high workload or the time taken to process a job is high.This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system.The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism.The resource allocation problem is modeled as a graph that can be used by the ant to deliver its pheromone.This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element.The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job.EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form.The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job. …”
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    Monograph
  4. 4

    Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation by Zhanuzak, Raiymbek, Ala'anzy, Mohammed Alaa, Othman, Mohamed, Algarni, Abdulmohsen

    Published 2024
    “…Unlike benchmark algorithms that rely on static VM selection or post-hoc relocation of cloudlets, the EDLB algorithm dynamically identifies optimal cloudlet placement in real-time. …”
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    Article
  5. 5

    Optimal design of EV aggregator for real-time peak load shaving and valley filling by Solanke T.U., Khatua P.K., Ramachandaramurthy V.K., Yong J.Y., Kanesan J., Tariq M., Kasinathan P.

    Published 2023
    “…Battery management systems; Dynamic loads; Energy management systems; Genetic algorithms; Landforms; Optimal systems; Power electronics; Deterministic optimization; Fluctuating loads; Grid-connected; Matlab Simulink models; Optimal design; Optimization algorithms; Real-time application; State of charge; Electric power transmission networks…”
    Conference Paper
  6. 6

    An enhanced ant colony system algorithm for dynamic fault tolerance in grid computing by Saufi, Bukhari

    Published 2020
    “…Ant colony system (ACS), a variant of ant colony optimization (ACO), is one of the promising algorithms for fault tolerance due to its ability to adapt to both static and dynamic combinatorial optimization problems. …”
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    Thesis
  7. 7

    Optimization Of Bar Linkage By Using Genetic Algorithms by Ramasamy, Mugilan

    Published 2005
    “…Two types of problems are chosen to optimize in this thesis. First problem is optimization of four bar linkage under static loading condition and second problem is optimization of four bar linkage under dynamic condition without loading. …”
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    Monograph
  8. 8

    Optimizing energy and reserve minimization in a sustainable microgrid with electric vehicle integration: dynamic and adjustable manta ray foraging algorithm by Abed, Adnan Ajam, Suwaed, Mahmood Sh., Al-Rubaye, Ameer H., Awad, Omar I., Mohammed, M.N, Hai, Tao, Kadirgama, Kumaran, Karah Bash, Ali A. H.

    Published 2023
    “…The growing presence of EVs in regional microgrids introduces increased variability and uncertainty in the areas’ load profiles. This paper presents a novel approach for optimizing energy and reserve minimization in a sustainable integrated microgrid with electric vehicles (EVs) by the use of the dynamic and adjustable Manta Ray Foraging (DAMRF) algorithm. …”
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    Article
  9. 9

    Optimized Load Balancing based Task Scheduling in Cloud Environment by Noraziah, Ahmad, Sultan, Elrasheed Ismail, Faisal, Alamri, Abdalla, Ahmed N.

    Published 2014
    “…In addition, the salient feature of this algorithm is to optimize node available throughput dynamically using MatLab10A software. …”
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    Article
  10. 10

    Resource scheduling algorithm with load balancing for cloud service provisioning by Priya, V., Sathiya Kumar, C., Kannan, R.

    Published 2019
    “…Increasing utilization of Virtual Machines through effective and fair load balancing is then achieved by dynamically selecting a request from a class using Multidimensional Queuing Load Optimization algorithm. …”
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    Article
  11. 11

    A dynamic replication aware load balanced scheduling for data grids in distributed environments of internet of things by Bakhshad, Said, Noor, Rafidah Md, Akhundzada, Adnan, Saba, Tanzila, Ahmedy, Ismail, Haroon, Faisal, Nazir, Babar

    Published 2018
    “…We propose a novel dynamic Replication Aware Load Balanced Scheduling (DRALBS) algorithm, that considers the replica location dynamically at the time of scheduling of the job. …”
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    Article
  12. 12

    Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control by Naidu, K., Mokhlis, Hazlie, Bakar, Ab Halim Abu

    Published 2014
    “…This paper presents the implementation of multiobjective based optimization of Artificial Bee Colony (ABC) algorithm for Load Frequency Control (LFC) on a two area interconnected reheat thermal power system. …”
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    Article
  13. 13

    An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions by Mannan M., Roslan M.F., Reza M.S., Mansor M., Jern K.P., Hossain M.J., Hannan M.A.

    Published 2024
    “…This study presents an optimal schedule controller for microgrid energy management, utilizing the Binary Particle Swarm algorithm (BPSO) to minimize costs and ensure optimal power delivery to loads. …”
    Conference Paper
  14. 14

    An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm by Najeeb, Mushtaq, Shahooth, Mohammed, Mohaisen, Arrak, Ramdan, Razali, Hamdan, Daniyal

    Published 2016
    “…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
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    Article
  15. 15

    Enhanced ant colony optimization for grid load balancing by Mohamed Din, Aniza, Ku-Mahamud, Ku Ruhana, Abdul Nasir, Husna Jamal

    Published 2011
    “…This paper proposes an Enhanced Ant Colony Optimization (EACO) algorithm for dynamic schedulling and load balancing in a grid computer system. …”
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    Conference or Workshop Item
  16. 16

    Dynamic control and performance of dual active bridge converter based particle swarm optimization by Suliana, Ab Ghani, Hamdan, Daniyal, Norazila, Jaalam, Norhafidzah, Mohd Saad, Nur Huda, Ramlan

    Published 2022
    “…This paper presents analysis of the dynamic response of the isolated bidirectional dual active bridge (DAB) DC-DC converter using particle swarm optimization (PSO) algorithm. …”
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    Conference or Workshop Item
  17. 17

    Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

    Published 2023
    “…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
    text::Thesis
  18. 18

    A comparative evaluation of heuristic and metaheuristic job scheduling algorithms for optimized resource management in cloud environments by Haque, Najmul, Zafril Rizal, M. Azmi, Murad, Saydul Akbar

    Published 2026
    “…Numerous scheduling methodologies have been developed, each targeting specific performance objectives such as reducing makespan, minimizing flow time, decreasing deadline violations, and optimizing resource utilization. The selection of an appropriate scheduling algorithm is crucial for ensuring optimal performance, scalability, and resource efficiency as cloud environments become increasingly complex and dynamic. …”
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    Conference or Workshop Item
  19. 19

    Enhanced Load-Aware Handover Algorithm for High-Density IEEE 802.11 ESS Networks by Derrick Qin Sheng, Wong, Chong Eng, Tan

    Published 2025
    “…This paper introduces a novel implementation of a load-aware handover strategy that integrates both RSSI and real-time access point (AP) load metrics to optimize handover decisions. …”
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    Article
  20. 20

    Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach by Ab Ghani, Mohd Ruddin, Hindi, K. S.

    Published 1991
    “…The solution algorithm is based on Lagrangian relaxation and on exploiting the intimate relationship between optimizing the dual Lagrangian function and Dantzig-Wolfe decomposition. …”
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    Article