Search Results - optimal ((((((self algorithm) OR (new 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

    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
    “…In this paper, a new algorithm, Intelligent agent AntNet based Routing Algorithm (IANRA) is proposed to enhance load balancing strategy in Wireless Networks (WNs). …”
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    Conference or Workshop Item
  3. 3

    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
  4. 4

    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 can effectively be used to tackle large scale optimization problems.Computational tests show promises of the new algorithm.…”
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    Article
  5. 5

    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
    “…This approach offers good opportunity to explore a large area of the search space. This paper proposes a new generic algorithmic approach that utilized multiple ant colonies with several new interaction techniques. …”
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    Article
  6. 6

    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 new hybrid algorithm integrates the good features of both standard optimization strategies, thus producing better possible solutions. …”
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    Conference or Workshop Item
  7. 7

    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
  8. 8

    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
    “…In order produce a global optimal solution of AUC, the self-adaptive strategy was proposed to serve as a new mutation technique responsible to provide a new population for discrete artificial bee colony. …”
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    Thesis
  9. 9

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

    Published 2010
    “…This thesis addresses the issues associated with search stagnation problem that ACO algorithms suffer from. In particular, it proposes the use of multiple interacted ant colonies as a new algorithmic framework. …”
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    Thesis
  10. 10

    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
    “…In order produce a global optimal solution of AUC, the self-adaptive strategy was proposed to serve as a new mutation technique responsible to provide a new population for discrete artificial bee colony. …”
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    Book Section
  11. 11

    Formulation of metaheuristic algorithms based on artificial bee colony for engineering problems by Lee, Wei Wen

    Published 2024
    “…The Artificial Bee Colony (ABC) algorithm is a powerful metaheuristic optimization technique inspired by the honeybee foraging behaviour. …”
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    Thesis
  12. 12

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

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
  13. 13
  14. 14

    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…New young queens are produced by the colony that migrates to establish new colonies after local optimum solution reached to start new local search. …”
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    Thesis
  15. 15

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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    Article
  16. 16

    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
  17. 17

    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
  18. 18

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…Apart from the size of the optimization problem, how the swapping interval affects the dynamic optimization by the ant algorithms is also investigated. …”
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    Thesis
  19. 19

    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…This project proposed a new optimization technique based on the ant colony algorithm for solving single-pass turning optimization problems. …”
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    Undergraduates Project Papers
  20. 20

    Ant colony optimization algorithm for rule based classification: Issues and potential by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2018
    “…Classification rule discovery using ant colony optimization (ACO) imitates the foraging behavior of real ant colonies. …”
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    Article