Search Results - optimal ((((path algorithm) OR (means algorithm))) OR (bees algorithm))

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  1. 1

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

    Published 2021
    “…To reduce the optimization time of the tours created by the artificial bee colony algorithm, the fixed-radius near neighbor 2-opt algorithm was used as well. …”
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    Article
  2. 2

    Optimization of drilling path using the bees algorithm by Kamaruddin, Shafie, Rosdi, Mohamad Naqiuddin, Sukindar, Nor Aiman

    Published 2021
    “…This study uses the Bees Algorithm to find the best sequence of drilling holes (minimum total path length) and the results found are compared with the result of other algorithms. …”
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    Article
  3. 3

    Application of the Bees Algorithm to find optimal drill path sequence by Zainal Abidin, Muhammad Harith, Kamaruddin, Shafie, Adam Malek, Afiqah, Sukindar, Nor Aiman

    Published 2024
    “…The main finding of the study is that the Bees Algorithm found optimal drill path length and minimum machining time comparable to the results of the other algorithms for the 5 × 5, 7 × 7 and 9 × 9 problems. …”
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    Proceeding Paper
  4. 4

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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    Article
  5. 5

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

    Published 2019
    “…The main idea in this algorithm is the indirect communication between the ants which is established by the means of pheromones in finding the shortest path between their nest and food [14]. …”
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    Monograph
  6. 6

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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    Thesis
  7. 7

    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
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    Conference or Workshop Item
  8. 8

    Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

    Published 2007
    “…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
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    Conference or Workshop Item
  9. 9
  10. 10

    Power-efficient wireless coverage using minimum number of uavs by Sawalmeh A., Othman N.S., Liu G., Khreishah A., Alenezi A., Alanazi A.

    Published 2023
    “…Antennas; Disasters; Genetic algorithms; Iterative methods; K-means clustering; Particle swarm optimization (PSO); 3-D placements; Artificial bee colony; Efficient 3d placement; Genetic algorithm; K-means; Particle swarm optimization; Placement algorithm; Power efficient; Unmanned aerial vehicle; Wireless coverage; Unmanned aerial vehicles (UAV); algorithm; animal; bee; Algorithms; Animals; Bees; Unmanned Aerial Devices…”
    Article
  11. 11

    Optimization grid scheduling with priority base and bees algorithm by Ahmed, Mohammed Shihab

    Published 2014
    “…The main aim of this current research to propose an optimization of the initial scheduler for grid computing using the bees algorithm. …”
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    Thesis
  12. 12

    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

    Published 2024
    “…This study aims to evaluate the effectiveness of two optimization algorithms, artificial bee colony (ABC) and spiral dynamic algorithm (SDA), in controlling the position of a flexible-link manipulator. …”
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    Article
  13. 13

    Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

    Published 2007
    “…In this paper, GA has been applied to find the minimum path, then result will be compared with Dijkstra's algorithm are presented.…”
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    Thesis
  14. 14

    A generalized laser simulator algorithm for optimal path planning in constraints environment by Aisha, Muhammad

    Published 2022
    “…The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. …”
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    Thesis
  15. 15

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…After optimizing the proposed fuzzy model by means ofgenetic algorithm, the resulted planner produces shorter paths in shorter runtimes with limited variations in results of different runs of the planner. …”
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    Thesis
  16. 16

    A review on path planning and obstacle avoidance algorithms for autonomous mobile robots by Anis Naema Atiyah, Rafai, Noraziah, Adzhar, Nor Izzati, Jaini

    Published 2022
    “…This paper reviews the mobile robot navigation approaches and obstacle avoidance used so far in various environmental conditions to recognize the improvement of path planning strategists. Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). …”
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    Article
  17. 17

    Multi objective bee colony optimization framework for grid job scheduling by Alyaseri, Sana, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.…”
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    Conference or Workshop Item
  18. 18

    A review : On intelligent mobile robot path planning techniques by Muhammad, Aisha, Ali, Mohammad A.H., Shanono, Ibrahim Haruna

    Published 2021
    “…The artificial intelligence methods such as genetic algorithm (GA), fuzzy logic (FL), ant colony optimization (ACO), neural network (NN), firefly algorithm (FA), particle swarm optimization (PSO), bacterial foraging optimization (BFO), artificial bee colony (ABC), and other miscellaneous algorithms are reviewed. …”
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  19. 19

    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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    Thesis
  20. 20

    An application of grey wolf optimizer for commodity price forecasting by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Yusof, Yuhanis

    Published 2015
    “…Over the recent decades, there are many nature inspired optimization algorithms have been introduced.In this study, a newly algorithm namely Grey Wolf Optimizer (GWO) is employed for gasoline price forecasting.The performance of GWO is compared against the results produced by Artificial Bee Colony (ABC) algorithm and Differential Evolution (DE) algorithm. …”
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    Article