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  1. 1

    A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

    Published 2008
    “…Multiple ant colonies optimization is an extension of the Ant Colony Optimization framework It offers a good opportunity to improve the ant colony optimization algorithms by encouraging the exploration of a wide area of the search space without losing the chance of exploiting the history of the search.This paper proposes a new multiple ant colonies optimization algorithm that is based on ant colony system and utilizes ave rage pheromone evaluation mechanism.The new algorithm divides the ants’ populations into multiple ant colonies and can be used to tackle large volume combinatorial optimization problems effectively. …”
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    Conference or Workshop Item
  2. 2

    Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

    Published 2008
    “…The new algorithm is based on the ant colony system and utilizes average and maximum pheromone evaluation mechanisms. …”
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    Article
  3. 3

    Hybrid ant colony optimization algorithm for container loading problem by Yap, Ching Nei

    Published 2012
    “…It was showed that the proposed HACO algorithm has the capability in solving the CLP.…”
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    Thesis
  4. 4

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

    Published 2012
    “…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 other ant based algorithm, in terms of resource utilization. …”
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    Monograph
  5. 5
  6. 6

    Stagnation control using interacted multiple ant colonies by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

    Published 2009
    “…Stagnation is a common problem that all ant algorithms suffer from regardless of their application domain.This paper proposes a new algorithmic approach that can effectively be used to tackle combinatorial optimization problems with a good chance to control the stagnation. …”
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    Conference or Workshop Item
  7. 7

    New heuristic function in ant colony system for the travelling salesman problem by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Ant Colony System (ACS) is one of the best algorithms to solve NP-hard problems.However, ACS suffers from pheromone stagnation problem when all ants converge quickly on one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic values to calculate the probability of choosing the next node. …”
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  8. 8

    Big data clustering using grid computing and ant-based algorithm by Ku-Mahamud, Ku Ruhana

    Published 2013
    “…This paper presents a framework for big data clustering which utilizes grid technology and ant-based algorithm.…”
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  9. 9

    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
  10. 10

    Power line faults classification by neural network train by Ant Colony Optimization by Nasirudin, Mohd Syafiq

    Published 2017
    “…The characteristic of ACO algorithms is their explicit use of elements of previous solutions. …”
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    Student Project
  11. 11

    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 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
  12. 12

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

    Published 2011
    “…A simulation environment was developed to test the performance of the algorithm against another ant based algorithm in terms of resource utilization and to determine how different values of evaporation rate resource utilization. …”
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    Conference or Workshop Item
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    An Exploration Technique for the Interacted Multiple Ant Colonies Optimization Framework by Aljanaby, A, Ku-Mahamud, KR, Norwawi, NM

    Published 2024
    “…These tests also show the capability of IMACO to outperform other well known ant algorithms like ant colony system and max-min ant system.…”
    Proceedings Paper
  15. 15

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

    Published 2011
    “…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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    Thesis
  16. 16

    An exploration technique for the interacted multiple ant colonies optimization framework by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md. Norwawi, Norita

    Published 2010
    “…In this framework several colonies of artificial ants are utilized. These colonies are working coopereatively to solve an optimization problem using some interaction technique. …”
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    Conference or Workshop Item
  17. 17

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…An example to apply the Ant Colony Algorithm to the problem has been presented at the end of the paper to give clear picture from the application of the system and its efficiency. …”
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    Undergraduates Project Papers
  18. 18

    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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    Conference or Workshop Item
  19. 19

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

    Published 2011
    “…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion 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 other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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    Monograph
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