Search Results - optimal ((((self algorithm) OR (colony algorithm))) OR (_ algorithm))

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  1. 1

    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
  2. 2

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
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  3. 3

    QoS based fair load-balancing: paradigm to IANRA routing algorithm for wireless networks (WNs) by Moghanjoughi, Ayyoub Akbari, Khatun, Sabira, Mohd Ali, Borhanuddin, Raja Abdullah, Raja Syamsul Azmir

    Published 2008
    “…IANRA is based on Ants behaviour with some important factors such as: the specific self-organizing behaviour of ant colonies, the shortest path discovery and the related framework of Ant Colony Optimization (ACO). …”
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    Conference or Workshop Item
  4. 4

    A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots by Ismail, Amelia Ritahani, Tumian, Afidalina

    Published 2019
    “…According to [13], the two best-known swarm intelligence algorithms are Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO). …”
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    Monograph
  5. 5
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    Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi M... by Mohammed, Daw Saleh Sasi

    Published 2016
    “…The newly designed algorithm is termed as the discrete artificial bee colony associated with selfadaptive strategy (DABCSAS). …”
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    Thesis
  7. 7

    Computational intelligence of probabilistic simulation in demand side management for avoided utility cost improvisation in a generation operating system planning / Daw Saleh Sasi M... by Sasi Mohamme, Daw Saleh

    Published 2017
    “…The newly designed algorithm is termed as the discrete artificial bee colony associated with selfadaptive strategy (DABCSAS). …”
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    Book Section
  8. 8

    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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  9. 9

    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
    “…This algorithm synergizes the ABC algorithm and Artificial Rabbits Optimization (ARO) algorithm. …”
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  10. 10

    Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi by Mohamad Fauzi, Noor Shafiqa Fazlien

    Published 2020
    “…The results have shown that the Ant Colony Optimization Algorithm produced a better predictive accuracy. …”
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    Thesis
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    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…They are: Global Guided Artificial Bee Colony (GGABC), Improved Gbest Guided Artificial Bee Colony (IGGABC) and Artificial Smart Bee Colony (ASBC) algorithm. …”
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  13. 13

    Interacted multiple ant colonies optimization approach to enhance the performance of ant colony optimization algorithms by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md. Norwawi, Norita

    Published 2010
    “…One direction of ant colony optimization researches is dividing the ants’ population into several colonies. …”
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    Article
  14. 14

    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
  15. 15

    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
  16. 16

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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    Article
  17. 17

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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    Article
  18. 18

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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    Article
  19. 19

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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  20. 20

    Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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