Search Results - (( (evolution OR solution) interaction ant algorithm ) OR ( java implication based algorithm ))

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  1. 1

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

    Published 2010
    “…ACO algorithms generate a good solution at the early stages of the algorithm execution but unfortunately let all ants speedily converge to an unimproved solution. …”
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    Thesis
  2. 2

    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 paper proposes a new generic algorithmic approach that utilized multiple ant colonies with several new interaction techniques. …”
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    Article
  3. 3

    A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network by Jamaludin, Sallim, Rozlina, Mohamed, Roslina, Abd Hamid

    Published 2015
    “…Various graph clustering algorithms have been applied to protein interaction networks for detecting protein functional modules. …”
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    Conference or Workshop Item
  4. 4

    A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network by Jamaludin, Sallim, Rozlina, Mohamed, Che, Yahaya, Roslina, Abdul Hamid

    Published 2018
    “…Various graph clustering algorithms have been applied to protein interaction networks for detecting protein functional modules. …”
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    Article
  5. 5

    A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali by Mohamed Kamali, Mohd Zahurin

    Published 2015
    “…It has been found that by implementing the ACP algorithm, the solution predicted is approximately close or similar to the exact solution. …”
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    Thesis
  6. 6

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…Recently, in line with the upcoming field called Search based Software Engineering (SBSE), many newly strategies have been developed adopting specific optimization algorithm (e.g. Genetic Algorithm (GA), Ant Colony (AC), Simulated Annealling (SA), Particle Swarm Optimization, and Harmony Search Algorithm (HS) as their basis in an effort to generate the most optimal solution. …”
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    Article
  7. 7

    A review on autonomous mobile robot path planning algorithms by Noraziah, Adzhar, Yuhani, Yusof, Muhammad Azrin, Ahmad

    Published 2020
    “…In this paper, commonly use classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (AFP), and heuristics approaches such as genetic algorithm (GA), particle swarm optimization (PSO) approach and ant colony optimization (ACO) method are considered.It is observed that when it comes to dynamic environment where most of the information are unknown to the mobile robots before starting, heuristics approaches are more popular and widely used compared to classical approaches since it can handle uncertainty, interact with objects and making quick decision. …”
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    Article
  8. 8

    Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

    Published 2018
    “…The results showed that the proposed PSO algorithm outperformed the other algorithms in terms of the optimal solutions and the convergence.…”
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    Article
  9. 9

    Problem Solving by Yahaya, Azizi

    Published 2010
    “…In everyday experiences, these steps may be implemented very flexibly, such that various steps may be repeated, may occur out of sequence, or may be implemented interactively. Although well-structured problems may have a clear path to solution, the route to solution may still be difficult to follow. …”
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    Article
  10. 10

    An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation by Kamal Z., Zamli, Fakhrud, Din, Kendall, Graham, Ahmed, Bestoun S.

    Published 2017
    “…Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t-way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), and Harmony Search (HS). …”
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    Article
  11. 11

    Recent advances of whale optimization algorithm, its versions and applications by Alyasseri Z.A.A., Ali N.S., Al-Betar M.A., Makhadmeh S.N., Jamil N., Awadallah M.A., Braik M., Mirjalili S.

    Published 2024
    “…The main idea behind the SI is to transfer the interactions between living organisms into a mathematical model that can find the optimal solution for real-world problems based on biological behavior such as ants, birds, and fish. …”
    Book chapter
  12. 12

    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar by Abu Bakar, Nordin (Prof. Madya Dr.)

    Published 2012
    “…Others have been looking beyond into the animal kingdom to learn how ants find their way to the food source.…”
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    Research Reports
  13. 13
  14. 14

    A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

    Published 2019
    “…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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    Thesis
  15. 15