Search Results - (( basic (equalization OR localization) based algorithm ) OR ( using solution using algorithm ))

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  1. 1

    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. …”
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    Thesis
  2. 2

    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim by Kamarzaman, Nur Atharah, Sulaiman, Shahril Irwan, Ibrahim, Intan Rahayu

    Published 2021
    “…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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    Article
  3. 3

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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    Thesis
  4. 4

    Implementing Kempe chain neighborhood structure in harmony search for solving curriculum based course timetabling by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2013
    “…An essential aspect that contributes to the success of meta-heuristic algorithm over a curriculum-based course timetabling problem is determined by the neighborhood structure used.The basic neighborhood structures such as move and swap between lectures has no method for escaping from local minima or optimum that restricts the improvement of current solutions. …”
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    Conference or Workshop Item
  5. 5

    Mathematical formulation of tabu search in combinatorial optimization by Ismail, Zuhaimy

    Published 2008
    “…CARP is known to be Non-deterministic Polynomialtime hard (NP-hard) where solutions are obtained through heuristic methods. Tabu Search (TS) is a heuristic method based on the use of prohibition-based techniques and basic heuristics algorithms like local search. …”
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    Monograph
  6. 6
  7. 7

    Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic Algorithm by Abed I.A., Koh S.P., Sahari K.S.M., Jagadeesh P., Tiong S.K.

    Published 2023
    “…A method based on a modified electromagnetism-like with two-direction local search algorithm (MEMTDLS) and genetic algorithm (GA) is proposed to determine the optimal time of task scheduling for dual-robot manipulators. …”
    Article
  8. 8

    Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

    Published 2022
    “…The study also developed an algorithm for predictive EMS using fuzzy model predictive control technique based on regression algorithm. …”
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    Thesis
  9. 9

    Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

    Published 2009
    “…Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
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    Thesis
  10. 10

    Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan Yin Keong, Tan Yin

    Published 2012
    “…A continuous time model based on transfer events is used to represent the scheduling problem and this model is a nonconvex MINLP model which presents multiple local optima. …”
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    Final Year Project
  11. 11

    Quality Of Service Provisioning Scheme For Real-Time Applications in IEEE 802.11 Wireless Local Area Network by Ng, Roger Cheng Yong

    Published 2006
    “…The SNT adapts contention parameters of individual ACs based on the network load in a basic service set (BSS). …”
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    Thesis
  12. 12

    Design and development of single-axis solar tracking system and water level control for application of line focus concentrator for solar desalination process by Muhammad Adam, Zahari

    Published 2017
    “…The tracking algorithm determines the angles which are used to determine the position of solar tracker. …”
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    Undergraduates Project Papers
  13. 13

    Public healthcare facility planning in Malaysia : Using location allocation models / S. Sarifah Radiah Shariff by S. Sarifah Radiah, Shariff

    Published 2012
    “…The results from CPLEX are observed to violate some of facilities’ constraint, thus making the solutions infeasible. A heuristic based on Genetic Algorithm (GA) is proposed and some computational analysis is carried out to gauge the performance of the existing facilities. …”
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    Thesis
  14. 14

    Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant by Morshidi, Malik Arman

    Published 2007
    “…Morphological operation is applied to remove the small blobs. Prior to localization of the base of young corn tree, skeletonizing operation is performed to get the basic shape of the object. …”
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    Thesis
  15. 15

    Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian by Tey, Siew Kian

    Published 2009
    “…This optimal state estimate and corrected data base are then used by the security monitoring and operation and control functions of the center.Most state estimation programs in practical use are formulated as overdetermined systems (Pozrikidis, 2008) of nonlinear equations and solved as weighted least square problems (refer to section 2.1.1).This research involves finding the least squares solution of the power system state estimation problem, HTR-1HDx = HTR-1 [z - f (x)] (refer to section 2.3.1) and to develop a program to implement the said algorithm. …”
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    Thesis
  16. 16

    A hybrid range-free algorithm using dynamic communication range for wireless sensor networks by Fengrong, Han, Izzeldin Ibrahim, Mohamed Abdelaziz, Xinni, Liu, Kamarul Hawari, Ghazali, Hao, Wang

    Published 2020
    “…Distance-Vector Hop (DV-Hop) is a representative range-free localization algorithm, which is widely utilized to locate node position in location-based application. …”
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    Article
  17. 17

    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. …”
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    Article
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    Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks by Han, Fengrong

    Published 2022
    “…Nevertheless, as the representative range-free localization scheme, Distance Vector-Hop (DV-Hop) localization algorithm demonstrates extremely poor localization accuracy under anisotropic wireless sensor networks. …”
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    Thesis
  20. 20

    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.…”
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    Conference or Workshop Item