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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
    “…P-Median problem will be used as the main case study in implementing one of the Bee-Inspired algorithms to prove, illustrate example and show the characteristics of the selected concept…”
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  2. 2
    Two level Differential Evolution algorithms for ARMA parameters estimatio

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. …”
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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
    “…The Artificial Bee Colony (ABC) algorithm has gained widespread attention and has been applied in various fields due to its ability to achieve excellent global optimization results and ease of implementation. …”
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  4. 4
    Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin

    Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin by Mohd Zin, Nurul Syakira

    Published 2022
    “…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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  5. 5
    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation

    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation by Kamaruddin, Shafie, Bahari, Muhammad Syahril, Pham, Duc Truong, Mohd Amin Hamzas, Mohd Fidzwan, Zakaria, S

    Published 2019
    “…The Bees Algorithm is a population-based optimisation algorithm inspired by the food foraging behaviour of honey bees. …”
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  6. 6
    Reliably optimal PMU placement using disparity evolution-based genetic algorithm

    Reliably optimal PMU placement using disparity evolution-based genetic algorithm by Matsukawa, Yoshiaki, Othman, Mohammad Lutfi, Watanabe, Masayuki, Mitani, Yasunori

    Published 2017
    “…The optimization model is solved for IEEE 118 standard bus system. …”
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  7. 7
    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…Global optimisation method includes differential evolution algorithm, which will be used in this research. …”
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  8. 8
    An improved bees algorithm local search mechanism for numerical dataset

    An improved bees algorithm local search mechanism for numerical dataset by Al-Dawoodi, Aras Ghazi Mohammed

    Published 2015
    “…Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental search techniques is based on the food foraging activities of bees. …”
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  9. 9
    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution

    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2014
    “…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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  10. 10
    A true annealing approach to the marriage in honey-bees optimization algorithm

    A true annealing approach to the marriage in honey-bees optimization algorithm by Teo, Jason Tze Wi, Hussein A. Abbass

    Published 2003
    “…The modified algorithm is tested using a group of randomly generated hard 3-SAT problems to compare its behavior and efficiency against previous implementations. …”
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  11. 11
    Optimization Of Fractional-Slot Permanent Magnet Synchronous Machine Using Analytical Sub-Domain Model And Differential Evolution

    Optimization Of Fractional-Slot Permanent Magnet Synchronous Machine Using Analytical Sub-Domain Model And Differential Evolution by Mohamed, Mohd Rezal

    Published 2019
    “…From the results obtained, the Analytical Sub-Domain Differential Evolution Algorithm (ASDEA) has better optimization technique capability compared with Analytical Sub-Domain Particle Swarm Optimization (ASPSO). …”
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  12. 12
    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm

    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm by Salami, Momoh Jimoh Eyiomika, Tijani, Ismaila, Isqeel , Abdullateef Ayodele, Aibinu, Abiodun Musa

    Published 2013
    “…The proposed algorithm involves a two level optimization scheme to search for both optimal network architecture and weights. …”
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  13. 13
    Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia

    Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

    Published 2024
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  14. 14
    Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin

    Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin by Mohd Zin, Nurul Syakira

    Published 2021
    “…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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  15. 15
    An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model

    An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model by Ayda, Emdadian, Ponnambalam, S. G., Kanagaraj, G.

    Published 2018
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  16. 16
    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
    “…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. 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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  17. 17
    Global gbest guided-artificial bee colony algorithm for numerical function optimization

    Global gbest guided-artificial bee colony algorithm for numerical function optimization by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…Recently, an attractive bio-inspired method—namely the Artificial Bee Colony (ABC)—has shown outstanding performance with some typical computational algorithms in different complex problems. …”
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  18. 18
    A holistic review on artificial intelligence techniques for well placement optimization problem

    A holistic review on artificial intelligence techniques for well placement optimization problem by Islam, J., Vasant, P.M., Negash, B.M., Laruccia, M.B., Myint, M., Watada, J.

    Published 2020
    “…Nature-inspired gradient-free optimization algorithms like particle swarm optimization, genetic algorithm, covariance matrix adaptation evolution strategy and differential evolution have been utilized in this area. …”
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  19. 19
    Optimization of handover algorithms in 3GPP long term evolution system

    Optimization of handover algorithms in 3GPP long term evolution system by Lin, Cheng-Chung, Sandrasegaran, Kumbesan, Mohd. Ramli, Huda Adibah, Basukala, Riyaj, Patachaianand, Rachod, Chen, Lu, Afrin, Toyoba Sohana

    Published 2011
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  20. 20
    Minimizing power loss using modified artificial bee colony algorithm / Nur Azlin Ashiqin Mohd Amin ...[et al.]

    Minimizing power loss using modified artificial bee colony algorithm / Nur Azlin Ashiqin Mohd Amin ...[et al.] by Mohd Amin, Nur Azlin Ashiqin, Jamaluddin, Siti Hafawati, Muhammat Pazil, Nur Syuhada, Mahmud, Norwaziah, Kimpol, Norhanisa

    Published 2021
    “…In this paper, the Modified Artificial Bee Colony (MABC) algorithm is implemented to solve the power system's optimal reactive power flow problem. …”
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