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    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

    Published 2012
    “…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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    Monograph
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    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
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    New heuristic function in ant colony system for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Alobaedy, Mustafa Muwafak

    Published 2012
    “…Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This paper focuses on enhancing the heuristic function where information about recent ants’ discoveries will be taken into account.Experiments were conducted using a simulator with dynamic environment features to mimic the grid environment.Results show that the proposed enhanced algorithm produce better output in term of utilization and make span.…”
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    Conference or Workshop Item
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    Resource management in grid computing using enhanced ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza, Abdul Nasir, Husna Jamal

    Published 2010
    “…Simulation approach has been used to test the performance of the algorithm. …”
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    Conference or Workshop Item
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    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Nowadays, many task allocation techniques are used but the most efficient technique needs to be figured out. Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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    Academic Exercise
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    Autonomous mobile robots path planning with integrative edge cloud-based ant colony optimization by Nor Azmi, Siti Nur Lyana Karmila, Anwar Apandi, Nur Ilyana, Rafique, Majid, Muhammad, Nor Aishah

    Published 2025
    “…To address these challenges, this study proposes an Integrative Edge Cloud-Based Ant Colony Optimization (IECACO) algorithm. IECACO incorporates a novel path retrieval mechanism and edge cloud computing infrastructure to minimize redundant path computation and improve convergence efficiency. …”
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    Article
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    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
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    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
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    Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

    Published 2015
    “…The proposed algorithms were evaluated against twelve metaheuristic algorithms in static (expected time to compute model) and dynamic (distribution pattern) grid computing environments. …”
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    Thesis
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    An evaluation of network load balancing through Ant Colony Optimization (ACO) based technique / Muhammad Nur Zikri Mohamad Hafizan by Mohamad Hafizan, Muhammad Nur Zikri

    Published 2020
    “…The results also show that the ACO algorithm was able to outperform the Randomized and Round Robin algorithm in all simulation configurations.…”
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    Student Project
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    A hybrid of Simple Constrained artificial bee colony algorithm and flux balance analysis for enhancing Lactate and Succinate in Escherichia Coli by Hon, Mei Kie, Mohd Saberi, Mohamad, Abdul Hakim, Mohamed Salleh, Choon, Yee Wen, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Omatu, Sigeru, Corchado, Juan Manuel

    Published 2018
    “…The hybrid algorithm employed the Simple Constrained Artificial Bee Colony (SCABC) algorithm, using swarm intelligence as an optimization algorithm to optimize the objective function, where lactate and succinate productions are maximized by simulating gene knockout in E. coli. …”
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    Book Chapter
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    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