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  1. 1
    Optimization of supply chain management by simulation based RFID with XBEE Network

    Optimization of supply chain management by simulation based RFID with XBEE Network by Soomro, Aftab Ahmed

    Published 2015
    “…In order to solve this problem, a simulation based “Multi-Colony Global Particle Swarm Optimization (MC-GPSO)” algorithm was developed. This algorithm computes the optimal results of objective functions in a scientific manner. …”
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  2. 2
    A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem

    A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

    Published 2023
    “…Hence, a hybrid optimization algorithm called Artificial Bee Rabbit Optimization (ABRO) is proposed in this paper. …”
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  3. 3
    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems

    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

    Published 2021
    “…To reduce the optimization time of the tours created by the artificial bee colony algorithm, the fixed-radius near neighbor 2-opt algorithm was used as well. …”
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  4. 4
    Local search manoeuvres recruitment in the bees algorithm

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

    Published 2011
    “…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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  5. 5
    The design and applications of the african buffalo algorithm for general optimization problems

    The design and applications of the african buffalo algorithm for general optimization problems by Odili, Julius Beneoluchi

    Published 2017
    “…Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. …”
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  6. 6
    Data Analysis using Particle Swarm Optimization Algorithm

    Data Analysis using Particle Swarm Optimization Algorithm by Tai, Zu Jie

    Published 2015
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  7. 7
    Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim

    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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  8. 8
    Basic concept of implementing Artificial Bee Colony (ABC) system in flow shop scheduling

    Basic concept of implementing Artificial Bee Colony (ABC) system in flow shop scheduling by Ho, Yoong Chow, Hasan, Sulaiman, Bareduan, Ahmad Salleh

    Published 2013
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  9. 9
    Hybrid artificial bee colony algorithm with branch and bound for two–sided assembly line balancing

    Hybrid artificial bee colony algorithm with branch and bound for two–sided assembly line balancing by Elteriki, Salem Abdulsalam

    Published 2018
    “…Recently, the artificial bee colony (ABC) algorithm was used in the solution process where it was considered as a very useful, effective and well-known algorithm. …”
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  10. 10
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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  11. 11
    Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization

    Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization by Salih, Sinan Q., Alsewari, Abdulrahman A., Al-Khateeb, Bellal, Mohamad Fadli, Zolkipli

    Published 2019
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  12. 12
    Hybrid DE-PEM algorithm for identification of UAV helicopter

    Hybrid DE-PEM algorithm for identification of UAV helicopter by Tijani, Ismaila, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus, Abdul Muthalif, Asan Gani

    Published 2014
    “…Design/methodology/approach – In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis. …”
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  13. 13
    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm

    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2002
    “…The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. …”
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  14. 14
    Recursive Subspace Identification Algorithm Using The Propagator Based Method

    Recursive Subspace Identification Algorithm Using The Propagator Based Method by Jamaludin, Irma Wani, Abdul Wahab, Norhaliza

    Published 2017
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  15. 15
    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm

    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2002
    “…The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. …”
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  16. 16
    Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani

    Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani by Seyed Asadollah, Abdiesfandani

    Published 2016
    “…The algorithm simulates two important tasks that are frequently used by the human experts to identify summarizing strategies used to produce the summary sentences: 1) sentences relevance identification; and 2) summarizing strategies identification. …”
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  17. 17
    Identification of non-linear dynamic systems using fuzzy system with constrained membership functions

    Identification of non-linear dynamic systems using fuzzy system with constrained membership functions by Yaakob, Mohd. Shafiek

    Published 2004
    “…This study deals with the use of the rule-based fuzzy system for the identification of non-linear dynamic systems. …”
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  18. 18
    Identification of continuous-time hammerstein system using sine cosine algorithm

    Identification of continuous-time hammerstein system using sine cosine algorithm by E. F., Junis, J. J., Jui, Mohd Helmi, Suid, Mohd Ashraf, Ahmad

    Published 2019
    “…This paper presents the development of identification of continuous-time Hammerstein systems based on Sine Cosine Algorithm (SCA). …”
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  19. 19
    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane

    Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2021
    “…This paper presents the identification of double pendulum overhead crane (DPOC) plant based on the hybrid Multi-Verse Optimizer with Sine Cosine Algorithm (HMVOSCA) using the continuous-time Hammerstein model. …”
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  20. 20
    Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm

    Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Mohamed Sultan, Mohamed Ali, Mohd Anwar, Zawawi, Mohd Falfazli, Mat Jusof

    Published 2021
    “…This paper presents the identification of the Thermoelectric Cooler (TEC) plant using a novel metaheuristic called hybrid Multi-Verse Optimizer with Sine Cosine Algorithm (hMVOSCA) based continuous-time Hammerstein model. …”
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