Search Results - (( wolf optimization based algorithm ) OR ( simulation optimization path algorithm ))

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  1. 1

    Robust multi-user detection based on hybrid grey wolf optimization by Ji, Yuanfa, Fan, Z ., Sun, X., Wang, S., Yan, S., Wu, S., Fu, Q., Kamarul Hawari, Ghazali

    Published 2020
    “…The simulation results show that the iteration times of the multi-user detector based on the proposed algorithm is less than that of genetic algorithm, differential evolution algorithm and Grey wolf optimization algorithm, and has the lower BER.…”
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    Book Chapter
  2. 2

    Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

    Published 2020
    “…Moreover, another new variant of CGWO, namely opposition based competitive grey wolf optimizer (OBCGWO), is proposed to enhance the performance of CGWO in feature selection. …”
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    Article
  3. 3

    A Hybrid Ant-Wolf Algorithm to Optimize Assembly Sequence Planning Problem by M. F. F., Ab Rashid

    Published 2017
    “…Purpose – This paper aims to optimize the assembly sequence planning (ASP) problem using a proposed hybrid algorithm based on Ant Colony Optimization (ACO) and Gray Wolf Optimizer (GWO). …”
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    Article
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    An Application of Grey Wolf Optimizer for Commodity Price Forecasting by Zuriani, Mustaffa, M. H., Sulaiman, Yuhani, Yusof

    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. …”
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    Article
  6. 6

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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    Article
  7. 7

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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    Article
  8. 8

    Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

    Published 2019
    “…Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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    Article
  9. 9

    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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    Monograph
  10. 10

    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
  11. 11

    An improved grey wolf optimizer with hyperbolic tangent updating mechanism for solving optimization problems by M. Z. M., Tumari, M. A., Ahmad, M. H., Suid

    Published 2021
    “…The original algorithm of Grey Wolf Optimizer (GWO) has a common problem which is too soon to trap in local optima. …”
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    Conference or Workshop Item
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    Grey Wolf Optimizer for Solving Economic Dispatch Problems by Wong, Lo Ing, M. H., Sulaiman, Mohd Rusllim, Mohamed, Hong, Mee Song

    Published 2014
    “…This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) which inspired by grey wolves (Canis lupus). …”
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    Conference or Workshop Item
  14. 14

    Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space by Zahari, Ammar, Ismail , Amelia Ritahani, Desia, Recky

    Published 2015
    “…A simulated robot in a simulated environment is used to test the algorithm that is to be developed. …”
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    Article
  15. 15

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

    Published 2022
    “…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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    Thesis
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    Hybrid conjugate gradient methods using strong Wolfe line search for Whale Optimization Algorithm / Wan Nur Athirah Wan Mohd Zakirudin by Wan Mohd Zakirudin, Wan Nur Athirah

    Published 2023
    “…Lastly, the implementation of LAMR-HS in the Whale Optimization Algorithm (WOA) aims to enhance the convergence speed, ultimately demonstrating the successful hybridization between the two algorithms.…”
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    Thesis
  17. 17

    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    Published 2016
    “…Therefore, the IE algorithm exhibits significant potential for UAV path planning optimization…”
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    Thesis
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    Route optimization using shortest path method / Muhamad Faisal Amin Shakri by Shakri, Muhamad Faisal Amin

    Published 2025
    “…Each algorithm was tested to compute the shortest path, with results indicating that while all algorithms arrive at the same optimal route, their efficiency differs. …”
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    Thesis
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