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  1. 1

    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
  2. 2

    Interacted Multiple Ant Colonies for Search Stagnation Problem by Aljanabi, Alaa Ismael

    Published 2010
    “…The experimental results show the superiority of the proposed approach than existing one colony ant algorithms like the ant colony system and max-min ant system. …”
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    Thesis
  3. 3

    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

    Published 2021
    “…This study seeks to solve this problem using Artificial Bee Colony (ABC) Algorithm along with the proposed Discrete Nearest Neighborhood Algorithm (DNNA). …”
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    Article
  4. 4

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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    Article
  5. 5

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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    Thesis
  6. 6

    Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani by Abdul Ghani, Nur Syafiqah

    Published 2021
    “…The results have shown that the Ant Colony Optimization Algorithm produced a better predictive accuracy. …”
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    Student Project
  7. 7

    Performance analysis of ant colony's algorithm: load-balancing in QoS-based wireless mesh networks routing by Moghanjoughi, Ayyoub Akbari, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir

    Published 2008
    “…The design of the algorithm is based on: the specific self-organizing behavior of ant colonies, the shortest path discovery, and the related framework of ant colony optimization (ACO). …”
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    Article
  8. 8

    A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

    Published 2023
    “…The Artificial Bee Colony (ABC) algorithm has gained widespread attention and has been applied in various fields due to its ability to achieve excellent global optimization results and ease of implementation. …”
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    Conference or Workshop Item
  9. 9

    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network by SALLIM, JAMALUDIN

    Published 2017
    “…Ant colony optimization (ACO) is a metaheuristic algorithm that has been successfully applied to several types of optimization problems such as scheduling, routing, and more recently for solving protein functional module detection (PFMD) problem in protein-protein interaction (PPI) networks. …”
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    Thesis
  10. 10

    Heuristic-Based Ant Colony Optimization Algorithm For Protein Functional Module Detection In Protein Interaction Network by Sallim, Jamaludin

    Published 2017
    “…Ant colony optimization (ACO) is a metaheuristic algorithm that has been successfully applied to several types of optimization problems such as scheduling, routing, and more recently for solving protein functional module detection (PFMD) problem in protein-protein interaction (PPI) networks. …”
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    Thesis
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    Enhancement on the modified artificial bee colony algorithm to optimize the vehicle routing problem with time windows by Sankor, Salah Mortada Shahen

    Published 2022
    “…The vehicle routing problem with time windows (VRPTW) is a non-deterministictime hard (NP-hard) with combinatorial optimization problem (COP). The Artificial Bee Colony (ABC) is a popular swarm intelligence algorithm for COP. …”
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    Thesis
  13. 13

    Solving the travelling salesman problem by using artificial bee colony algorithm / Noor Ainul Hayati Mohd Naziri by Mohd Naziri, Noor Ainul Hayati

    Published 2021
    “…In this study, the Artificial Bee Colony (ABC) algorithm was used to resolve the TSP. …”
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    Student Project
  14. 14

    Experiment on modified artificial bee colony for better global optimisation by Shahrudin, Muhammad Shahrizan, Mahmuddin, Massudi

    Published 2014
    “…Although there are many works have been done in Artificial Bee Colony (ABC) algorithm, yet, there still an issue for faster convergence for this algorithm.This paper will present a modified ABC algorithm to find optimum value for optimisation function.This hybrid ABC algorithm will adapt the modification especially in searching mechanism and probability function.The modified algorithm is tested on general global optimisation functions.The result demonstrates that the proposed algorithm produces better convergence compared to the original algorithm.…”
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    Book Section
  15. 15

    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

    Published 2013
    “…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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    Thesis
  16. 16

    Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification by Nuaimi, Zakaria Noor Aldeen Mahmood Al, Abdullah, Rosni

    Published 2017
    “…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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    Article
  17. 17

    Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms by Sulaiman, Noorazliza

    Published 2017
    “…One of BIAs, artificial bee colony (ABC) optimization algorithm, has shown excellent performance in many applications compared to other optimization algorithms. …”
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    Thesis
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    Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

    Published 2017
    “…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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    Article
  20. 20

    Hybrid ant colony system and genetic algorithm approach for scheduling of jobs in computational grid by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2015
    “…Metaheuristic algorithms have been used to solve scheduling problems in grid computing.However, stand-alone metaheuristic algorithms do not always show good performance in every problem instance. …”
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    Article