Search Results - (( its application ((use algorithm) OR (bee algorithm)) ) OR ( job application using algorithm ))*

Refine Results
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7

    Bees algorithm for Forest transportation planning optimization in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

    Published 2021
    “…Algorithm is widely used in various areas due to its ability to solve classes of problems. …”
    Get full text
    Get full text
    Article
  8. 8

    Home buyer assistant using artificial bee colony algorithm / Muhammad Izzat Azri Azman by Azman, Muhammad Izzat Azri

    Published 2017
    “…The assistant will provide suitable house recommendation to a home buyer based on particular information house specification such as house price, locations neighbourhood and surrounding information. This project used Artificial Bee Colony Algorithms (ABC) by adapting the food foraging behaviour of bee in honey bee and find a suitable house for home buyer based on their requirement. …”
    Get full text
    Get full text
    Thesis
  9. 9
  10. 10

    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS by MEHMOOD SHAH, SYED NASIR

    Published 2012
    “…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
    Get full text
    Get full text
    Thesis
  11. 11

    Artificial Bee Colony Algorithm for Pairwise Test Generation by Alazzawi, Ammar K., Homaid, Ameen A. Ba, Alomoush, Alaa A., Alsewari, Abdulrahman A.

    Published 2017
    “…PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    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. …”
    Get full text
    Get full text
    Monograph
  13. 13
  14. 14
  15. 15

    Impatient job scheduling under cloud computing by Mahdi, Nawfal A.

    Published 2012
    “…The limitations of those algorithms were addressed and this leads to the proposition of an algorithm that has the ability to map the impatient jobs to virtual machines near its input, output, application, or forth party. …”
    Get full text
    Get full text
    Thesis
  16. 16

    Optimising a waste management system using the Artificial Bee Colony (ABC) algorithm by Mohamad Fadzil, Nur Hamisha Helanie

    Published 2025
    “…This study proposed the application of the Artificial Bee Colony (ABC) algorithm to address the Capacitated Vehicle Routing Problem (CVRP) in a real-world waste collection scenario. …”
    Get full text
    Get full text
    Student Project
  17. 17
  18. 18
  19. 19
  20. 20