Search Results - (( solution population selection algorithm ) OR ( java application using algorithm ))

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  1. 1

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis
  2. 2

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…It has been implemented in various applications such as scheduling. The flows of GA are using selection, crossover and mutation operators applied to populations of chromosomes. …”
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    Thesis
  3. 3

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…It has been implemented in various applications such as scheduling. The flows of GA are using selection, crossover and mutation operators applied to populations of chromosomes. …”
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    Thesis
  4. 4

    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…It has been implemented in various applications such as scheduling. The flows of GA are using selection, crossover and mutation operators applied to populations of chromosomes. …”
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    Thesis
  5. 5

    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. …”
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    Article
  6. 6

    Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

    Published 2018
    “…Like other population-based algorithms, WOA generate its population randomly during the exploration and exploitation phases, which could generate values far from the optimum solution or stuck the exploration around local optima. …”
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    Article
  7. 7

    Improved elitist genetic algorithm for reactive power planning in power system / Mohamad Fadhil Mohd Kamal by Mohd Kamal, Mohamad Fadhil

    Published 2010
    “…The EGA ensures the quality of the solution never deteriorates as the generations progress since the fittest solution of the current population is duplicated in the subsequent generations. …”
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    Thesis
  8. 8

    Neuro-fuzzy genetic algorithm by Varnamkhasti, Mohammad Jalali, Lee, Lai Soon

    Published 2009
    “…This paper proposes a new variant of GA: neuro-fuzzy genetic algorithm with sexual selection. The motivation of this algorithm is to maintain the population diversity throughout the search procedure. …”
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    Conference or Workshop Item
  9. 9

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
  10. 10

    Fuzzy genetic algorithms for combinatorial optimisation problems by Varnamkhasti, Mohammad Jalali

    Published 2012
    “…The computational results shown that, the proposed sexual selection and FGAs are competitive and capable of generating near optimal solutions.…”
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    Thesis
  11. 11
  12. 12

    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…The algorithm includes (i) a population update strategy which improves the movement of hawks in the search space, (ii) a parameter adjusting strategy to control the transition between exploration and exploitation, and (iii) a population generating method in producing the initial candidate solutions. …”
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    Thesis
  13. 13
  14. 14

    Performance evaluation of Black Hole Algorithm, Gravitational Search Algorithm and Particle Swarm Optimization by Zuwairie, Ibrahim, Mohamad Nizam, Aliman, Fardila, Naim, Sophan Wahyudi, Nawawi, Shahdan, Sudin

    Published 2015
    “…In BH algorithm, the best solution is selected to be the black hole and the rest of candidates which are called stars will be drawn towards the black hole. …”
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    Article
  15. 15

    A genetic algorithm with fuzzy crossover operator and probability by Varnamkhasti, Mohammad Jalali, Lee, Lai Soon, Abu Bakar, Mohd Rizam, Leong, Wah June

    Published 2012
    “…The results indicate that the proposed algorithm is effective in finding better quality solutions.…”
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    Article
  16. 16

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. …”
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    Thesis
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    Committee neural networks with fuzzy genetic algorithm. by Jafari , S.A., Mashohor , Syamsiah, Varnamkhasti, M. Jalali

    Published 2011
    “…In this paper, we propose a new technique for choosing the female chromosome during sexual selection to avoid the premature convergence in a genetic algorithm. …”
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    Article
  19. 19

    Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

    Published 2022
    “…Hence, this study proposed to modify the Firefly Algorithm (FA) along with the Correlation-based Feature Selection (CFS) filter for the gene selection task. …”
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    Thesis
  20. 20

    Enhancement on the modified artificial bee colony algorithm to optimize the vehicle routing problem with time windows by Sankor, Salah Mortada Shahen

    Published 2022
    “…This study proposes an enhanced Modified ABC (E-MABC) algorithm which includes (i) N-MABC that overcomes the shortage of neighborhood selection by exchanging the neighborhood structure between two different routes in the solution; (ii) MABC-ACS that solves the issues of knowledge absence in MABC population initialization by incorporating ant colony system heuristics, and (iii) PMABC which addresses the occasional stops proceeding to the global optimum by introducing perturbation that accepts an abandoned solution and jumps out of a local optimum. …”
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    Thesis