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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
    “…This report presents the first stage of an ongoing research which is the problem solving of highly complex tasks using Bee-Inspired algorithms. Bee-Inspired algorithms are partially referring to the nature of bee swarm behaviour. …”
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  2. 2
    Artificial Bee Colony Algorithm for Pairwise Test Generation

    Artificial Bee Colony Algorithm for Pairwise Test Generation by Alazzawi, Ammar K., Homaid, Ameen A. Ba, Alomoush, Alaa A., Alsewari, Abdulrahman A.

    Published 2017
    “…PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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  3. 3
    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics

    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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  4. 4
    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
    “…The major purpose of this research is to suggest a new t-way strategy to minimize the test cases. This is called hybrid artificial bee colony (HABC) strategy, which is based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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  5. 5
    Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm

    Pairwise Test Suite Generation Based on Hybrid Artificial Bee Colony Algorithm by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2020
    “…Complementing to the earlier researches, this paper proposes a new pairwise test suite generation called Pairwise Hybrid Artificial Bee Colony (PhABC) strategy based on hybridize of an Artificial Bee Colony (ABC) algorithm with a Particle Swarm Optimization (PSO) algorithm. …”
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  6. 6
    IMPLEMENTATION OF A TIME SERIES PREDICTION ALGORITHM FOR COVID-19 CONFIRMED CASES IN MALAYSIA : A PRELIMANARY STUDY AFTER THE RECOVERY MOVEMENT CONTROL ORDER

    IMPLEMENTATION OF A TIME SERIES PREDICTION ALGORITHM FOR COVID-19 CONFIRMED CASES IN MALAYSIA : A PRELIMANARY STUDY AFTER THE RECOVERY MOVEMENT CONTROL ORDER by Tee, Bee Lin

    Published 2020
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  7. 7
    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…The research’s primary objective is to construct a framework for prioritising test cases in regression testing using swarm intelligence that enhances test efficiency and effectiveness. …”
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  8. 8
    Implementing a T-Way Test Generation Strategy Using Bees Algorithm

    Implementing a T-Way Test Generation Strategy Using Bees Algorithm by Mohd Hazli, Mohamed Zabil, Kamal Z., Zamli

    Published 2013
    “…This paper discusses our experiences on implementation of Bees algorithm for generating test cases to detect t-way interaction faults (where t signifies the interaction strength). …”
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  9. 9
    Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm

    Optimal sizing and location of distributed generation for power loss minimization using bee colony algorithm by Mohamad Zunnurain Fauzi

    Published 2023
    “…MATLAB is used by the assigned ABC algorithm to run the programme. …”
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  10. 10
    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
    “…This paper presents statistical analysis on the performance of Bees Algorithm against the other sequence t-way strategies, in order to generate test cases.…”
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  11. 11
    Bee colony optimisation of the travelling salesman problem in light rail systems

    Bee colony optimisation of the travelling salesman problem in light rail systems by Wang, Chen, Leong, Kah Huo, Abdul-Rahman, Hamzah

    Published 2019
    “…Although various algorithms based on social insect species have successfully solved complex problems, bee behaviour in nature has inspired more significant solutions. …”
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  12. 12
    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support

    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2019
    “…Supplementing to earlier research work, this paper proposed a new pairwise test suite generation called pairwise hybrid artificial bee colony (PhABC) strategy based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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  13. 13
    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support

    PhABC: A Hybrid Artificial Bee Colony Strategy for Pairwise test suite Generation with Constraints Support by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A.

    Published 2019
    “…Supplementing to earlier research work, this paper proposed a new pairwise test suite generation called pairwise hybrid artificial bee colony (PhABC) strategy based on hybridize of an artificial bee colony (ABC) algorithm with a particle swarm optimization (PSO) algorithm. …”
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  14. 14
    Implementing a t-way test generation strategy using bees algorithm

    Implementing a t-way test generation strategy using bees algorithm by Zabil M.H.M., Zamli K.Z.

    Published 2023
    “…This paper discusses our experiences on implementation of Bees algorithm for generating test cases to detect t-way interaction faults (where t signifies the interaction strength). © SCRG Publication, 2013.…”
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  15. 15
    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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  16. 16
    Systematic Review of Enhancement of Artificial Bee Colony Algorithm Using Ant Colony Pheromone

    Systematic Review of Enhancement of Artificial Bee Colony Algorithm Using Ant Colony Pheromone by Alaidi A.H., Der C.S., Leong Y.W.

    Published 2023
    “…One method to enhance ABC is to borrow exploration technique from other algorithms. Researchers use pheromone, which is a technique used by Ant Colony optimization algorithm, to enhance ABC and addressed several aspects of using a pheromone to enhance ABC. …”
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  17. 17
    Improved tree routing protocol in zigbee networks

    Improved tree routing protocol in zigbee networks by Al-Harbawi, Mostafa Kamil Abdulhusain

    Published 2010
    “…ImpTR protocol uses an approach to select next hope depending on new algorithm and uses the same tree topology construction for distributing address to all sensor nodes in the network. …”
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  18. 18
    Data Analysis using Particle Swarm Optimization Algorithm

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

    Published 2015
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  19. 19
    T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm

    T-way strategy for sequence input interactions test case generation adopting fish swarm algorithm by Rahman, Mostafijur, Sultana, Dalia, Sabira, Khatun, M. F. M., Jusof, Syamimi Mardiah, Shaharum, Nurhafizah, Abu Talip Yusof, Qaiduzzaman, Khandker M., Hasan, Md. Hasibul, Rahman, Md. Mushfiqur, Hossen, Md. Anwar, Begum, Afsana

    Published 2019
    “…In order to reduce test cases several T-way sequence input interaction strategies are explored, such as, Bee Algorithm(BA), Kuhn encoding (K) , ASP with Clasp , CP with Sugar, Erdem (ER) exact encoding, Tarui (TA) Method, U, UR, D and DR, Brain (BR). …”
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  20. 20
    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm

    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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    Academic Exercise
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