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  1. 1
    Application of Bee Colony Optimization (BCO) in NP-Hard Problems

    Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

    Published 2011
    “…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
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  2. 2
    Optimal design of step – cone pulley problem using the bees algorithm

    Optimal design of step – cone pulley problem using the bees algorithm by Yusof, Noor Jazilah, Kamaruddin, Shafie

    Published 2021
    “…Most of these algorithms were developed based on the collective behavior of social swarms of ants, bees, a flock of birds, and schools of fish. …”
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  3. 3
    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
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  4. 4
    Intelligent Optimization of Force Tracking Parameters for MR Damper Modelling using Firefly Algorithm

    Intelligent Optimization of Force Tracking Parameters for MR Damper Modelling using Firefly Algorithm by Mat Hussin, Ab Talib, Hanim, Mohd Yatim, Nik Mohd Ridzuan, Shaharuddin, Muhamad Sukri, Hadi, Intan Zaurah, Mat Darus, Annisa, Jamali

    Published 2020
    “…To overcome this problem, an intelligent optimization method known as firefly algorithm (FA) was used by this study to optimize the force tracking controller (FTC) parameters as to achieve the exact damping force of MR damper system. …”
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    Proceeding
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  5. 5
    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
    “…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
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  6. 6
    Algorithm in the fluidized-bed reactor for the polymerization of propylene

    Algorithm in the fluidized-bed reactor for the polymerization of propylene by Zanil, Mohd Fauzi, Chan, K.O., Hussain, Mohd Azlan

    Published 2019
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  7. 7
    Intelligent active force control of a robotic arm using genetic algorithm

    Intelligent active force control of a robotic arm using genetic algorithm by Mailah, Musa, Wong, Min Yee, Jamaluddin, Hishamuddin

    Published 2002
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  8. 8
    An Intelligent Active Force Control Algorithm to Control an Upper Extremity Exoskeleton for Motor Recovery

    An Intelligent Active Force Control Algorithm to Control an Upper Extremity Exoskeleton for Motor Recovery by Wan Hasbullah, Mohd Isa, Zahari, Taha, Ismail, Mohd Khairuddin, Anwar, P. P. A. Majeed, Khairul Fikri, Muhammad, Ali, Mohammed A. H., Jamaluddin, Mahmud, Zulkifli, Mohamed

    Published 2016
    “…A proportional-derivative (PD) architecture is employed in this study to investigate its efficacy performing joint-space control objectives. An intelligent AFC algorithm is also incorporated into the PD to investigate the effectiveness of this hybrid system in compensating disturbances. …”
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  9. 9
    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm

    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

    Published 2013
    “…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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  10. 10
    Artificial bee colony for inventory routing problem with backordering

    Artificial bee colony for inventory routing problem with backordering by Moin, N.H., Halim, H.Z.A.

    Published 2014
    “…We propose a metaheuristic method, Artificial Bee Colony (ABC) to solve the IRPB.The ABCalgorithm is a swarm based heuristics which simulates the intelligent foraging behaviour of a honey bee swarm and sharing that information of the food sources with the bees in the nest. …”
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  11. 11
    A fuzzy-active force based control architecture for characterizing a nonlinear MIMO system / Tengku Luqman Tengku Mohamed

    A fuzzy-active force based control architecture for characterizing a nonlinear MIMO system / Tengku Luqman Tengku Mohamed by Tengku Mohamed, Tengku Luqman

    Published 2016
    “…This study examines the modelling and control of a twin rotor multi-input multi-output (MIMO) system (TRMS). An intelligent Active Force Control (AFC) scheme is utilised to compensate disturbances that a conventional PID control algorithm alone is unable to due to the system’s highly nonlinear behaviour. …”
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  12. 12
    A quick gbest guided artificial bee colony algorithm for stock market prices prediction

    A quick gbest guided artificial bee colony algorithm for stock market prices prediction by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…In this respect, in the present manuscript, we propose an algorithm based on ABC to minimize the error in the trend and actual values by using the hybrid technique based on neural network and artificial intelligence. …”
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  13. 13
    Non-pressurized magnetorheological damper controlled using fuzzy semi active damping force estimator (fSADE)

    Non-pressurized magnetorheological damper controlled using fuzzy semi active damping force estimator (fSADE) by Saiful Anuar, Abu Bakar, Hishamuddin, Jamaluddin, Roslan, Abd Rahman, Pakharuddin, Mohd Samin, Ryosuke, Masuda, Hiromu, Hashimoto, Takeshi, Inaba

    Published 2012
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  14. 14
    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management

    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

    Published 2017
    “…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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  15. 15
    Review of Multi-Objective Swarm Intelligence Optimization Algorithms

    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…The MOSI algorithms are based on the integration of single objective algorithms and multi-objective optimization (MOO) approach. …”
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  16. 16
    Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation

    Hybrid Artificial Bee Colony Algorithm for t-Way Interaction Test Suite Generation by Alazzawi, A.K., Rais, H.M., Basri, S.

    Published 2019
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  17. 17
    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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  18. 18
    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network

    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

    Published 2020
    “…A total of 6 datasets were deployed to evaluate the effectiveness of the proposed algorithm. Results showed that EACS(TS) outperformed in terms of success rate, packet loss, latency, and energy efficiency when compared with single swarm intelligence routing algorithms which are Energy-Efficient Ant-Based Routing (EEABR), BeeSensor and Termite-hill. …”
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  19. 19
    Optimal economic environmental power dispatch by using artificial bee colony algorithm

    Optimal economic environmental power dispatch by using artificial bee colony algorithm by Hassan, Elia Erwani, Mohd Noor, Hanan Izzati, Hashim, Mohd Ruzaini, Sulaima, Mohamad Fani, Bahaman, Nazrulazhar

    Published 2024
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  20. 20
    Intelligent material handling mobile robot for industrial purpose with active force control capability

    Intelligent material handling mobile robot for industrial purpose with active force control capability by Mailah, Musa, Jamaluddin, Hishamuddin, Pitowarno, Endra, Purnomo, Didik Setyo

    Published 2005
    “…A number of disturbances in the form of vibratory and impact forces are deliberately introduced into the system to evaluate the system performances. …”
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