Search Results - parallel operation genetic algorithm

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    A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU) by Mohd Johar, Fauzi, Azmin, Farah Ayuni, Suaidi, Mohd Kadim, Shibghatullah, Abdul Samad, Ahmad, Badrul Hisham, Salleh, Siti Nadzirah, Abdul Aziz, Mohd Zainol Abidin, Md Shukor, Mahfuzah

    Published 2013
    “…This review attempts to study and analyse the behaviour of GA and parallel GA categories to work in GPU depending on the type of genetic algorithm. …”
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    Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources by Abed, Munther Hameed, Mohd Nizam Mohmad, Kahar

    Published 2022
    “…Additionally, an appropriate selection of GA operators was also experimented. The guide genetic algorithm (GGA) is not used to solve the unspecified dynamic UPMR. …”
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    Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

    Published 2015
    “…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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    Flexible job shop scheduling using priority heuristics and genetic algorithm by Farashahi, Hamid Ghaani

    Published 2010
    “…Then, the validation of proposed genetic algorithm with reinforced initial population (GA2) has been checked with random keys genetic algorithm (RKGA). …”
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    Regenerative braking strategy for electric vehicles using improved adaptive genetic algorithm by Taleghani, Hussein

    Published 2017
    “…The second strategy is based on Standard Genetic Algorithm (SGA). Lastly, the third strategy is utilizing Improved Adaptive Genetic Algorithm (IAGA). …”
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    FPGA Implementation of Multi-User Detection Genetic Algorithm Tool for SDMA-OFDM Systems by Alansi, M., Elshafiey, I., Al-Sanie, A., Mabrouk, A.

    Published 2016
    “…The data flow in GASOS is appropriate in pipelining and parallelization to reduce operational time. A new GASOS-based MUD hardware design for SDMA-OFDM systems is proposed using FPGA architecture. …”
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    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

    Published 2011
    “…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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    Parallel processing in Compute Unified Device Architecture (CUDA) for energy saving glass by Shibghatullah, Abdul Samad, Xia, Khoo Wen, Azmin, Farah Ayuni, Mohd Johar, Fauzi

    Published 2014
    “…However, genetic algorithm require a fast processing speed in order to cope with the process of creating new chromosome from the population and undergoes the selection, crossover and mutation operation processes. …”
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    Local search approaches for patient scheduling problem in parallel operating theatre by Alimin, Nur Neesha

    Published 2020
    “…In the first phase, pre-processing stage, combination of pre-processing stage with low-level heuristic and genetic algorithm are used.The different types of LS are applied in the second phase of scheduling. …”
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    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…On the other hand, the superior performance of the genetic algorithm that implements an extended diversity control mechanism demonstrates that more competent genetic algorithms can be designed through customized operators. …”
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    Optimal placement of static VAR compensator using genetic algorithms by Mustafa, Mohd. Wazir, Wong, Yan Chiew

    Published 2008
    “…The existence of the multiple solutions in the optimal placement of reactive power in the power system typically often get stuck at the local optimum rather than at the global optimum. Genetic Algorithms (GAs) are stochastic searching algorithms that make the searching process jumps randomly from point to point, thus allowing escape from the local optimum, and search for many sub-optimum points in parallel.This paper presents an evolutionary computation algorithm for enhancing voltage stability. …”
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    Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

    Published 2024
    “…Within the genetic algorithm framework, each timetable is represented as a chromosome, forming a population of potential timetables refined through successive generations by genetic operators like crossover and mutation. …”
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    Energy-aware scheduling optimization in hybrid flow shops using artificial bee colony algorithm by Mohd Abdul Hadi, Osman, Mohd Fadzil Faisae, Ab Rashid, Nik Mohd Zuki, Nik Mohamed, Muhammad Ammar, Nik Mu’tasim

    Published 2024
    “…Through an extensive computational experiment involving a well-known benchmark suite, the ABC algorithm demonstrated remarkable performance, consistently outperforming several popular metaheuristic algorithms, including Genetic Algorithms, Particle Swarm Optimization, Memetic Algorithms, and Whale Optimization Algorithm in 75% of the problems. …”
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    Bitwise-based Routing Algorithms in Optical Multistage Interconnection Network by Abed, Farzaneh

    Published 2007
    “…To avoid crosstalk in OMINs many algorithms have been proposed by many researchers such as the Four Heuristic, Simulated Annealing, Genetic, Remove Last Passes and Zero Algorithms. …”
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    Application of Artificial Neural Networks (ANN) for unit commitment prediction / Robert Engkiau by Engkiau, Robert

    Published 2003
    “…Results from existing Genetic Algorithm (GA) program were used as the NN training and testing data set. …”
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    Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh by Hisham Ahmad, Theeb Shehadeh

    Published 2018
    “…The obtained results are compared with the results of four algorithms. These algorithms are Genetic Algorithms (GA), Parallel Genetic Algorithm (PGA), Particle Swarm Optimization (PSO) and Accelerated Particle Swarm Optimization (APSO). …”
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