Search Results - (( basic optimization search algorithm ) OR ( evolution optimization clustering algorithm ))

Refine Results
  1. 1

    A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

    Published 2016
    “…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
    Get full text
    Get full text
    Article
  4. 4

    Basic firefly algorithm for document clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2015
    “…To address the shortcoming, this paper proposes a Basic Firefly (Basic FA) algorithm to cluster text documents.The algorithm employs the Average Distance to Document Centroid (ADDC) as the objective function of the search. …”
    Get full text
    Get full text
    Conference or Workshop Item
  5. 5

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
    Get full text
    Get full text
    Thesis
  7. 7

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

    Published 2018
    “…The optimal results obtained for constrained engineering problems as well as data clustering are very promising in terms of quality of solutions and convergence speed of the algorithm.…”
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm by Wang, Wei, Liu, Yao

    Published 2016
    “…Basically, Cuckoo searching algorithm imitates the natural evolution of a population with initial solutions. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  9. 9

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…In future, this work could be enhanced for better performances in both aspects using another variant of the PSO or other potential metaheuristic searching techniques such as Firefly Optimization, Bat Algorithm and etc.…”
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11
  12. 12

    Particle swarm optimization (PSO) for CNC route problem by Nur Azia Azwani, Ismail

    Published 2002
    “…The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  13. 13
  14. 14

    Tackling the berth allocation problem via harmony search algorithm by Ahmed, Bilal, Hamdan, Hazlina, Muhammed, Abdullah, Husin, Nor Azura

    Published 2024
    “…Harmony Search Algorithm (HSA) is one of the recent population-based optimization methods which inspired by modern-nature. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Descriptive analysis of patient diet trends at Pantai Hospital Ayer Keroh by Muhidin, Nurain Fatiha

    Published 2025
    “…Identifying the clustering results enables targeted meal planning based on patient group characteristics and helps optimize resources by understanding dietary demand within each cluster. …”
    Get full text
    Get full text
    Student Project
  17. 17

    Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

    Published 2011
    “…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  18. 18

    African Buffalo Optimization: A Swarm-Intelligence Technique by Odili, Julius Beneoluchi, M. N. M., Kahar, Shahid, Anwar

    Published 2015
    “…Our interest is in their organizational ability through two basic sounds in search of solutions. Experiments carried out using the novel algorithm in solving some benchmark Travelling Salesman’s Problem when compared with the results from some popular optimization algorithms show that the ABO was not only able to obtain better solutions but at a faster speed.…”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
    Get full text
    Get full text
    Thesis
  20. 20

    African Buffalo Optimization Algorithm for Tuning Parameters of a PID Controller in Automatic Voltage Regulators by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad

    Published 2016
    “…Though a recently-designed algorithm, the ABO has been effective and efficient in solving a number of search optimization problems. …”
    Get full text
    Get full text
    Get full text
    Article