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  1. 1

    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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    Thesis
  2. 2

    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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    Article
  3. 3

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

    Published 2023
    “…Therefore, a method which is Artificial Bee Colony (ABC) algorithm is proposed in this project for the optimal location and size of DG used in minimizing power losses and improve voltage profile. …”
    text::Final Year Project
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    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…Two multi-objective fed-batch models are also used as case studies to verify the performance of the proposed algorithm. …”
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    Thesis
  6. 6

    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
    “…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. …”
    Article
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    Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Kendall, Graham, Chuah, Joon Huang

    Published 2018
    “…In this work, an improved version of DE namely Backtracking Search Algorithm (BSA) has edged DE and other recent metaheuristics to emerge as superior optimization method. …”
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  9. 9

    Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy by Hossain Md.S., El-Shafie A., Mohtar W.H.M.W.

    Published 2023
    “…Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are used to compare the model performances. …”
    Article
  10. 10

    Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar by Vijyakumar, Kanendra Naidu

    Published 2015
    “…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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    Thesis
  11. 11

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

    Published 2015
    “…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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  12. 12

    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2018
    “…Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. …”
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  13. 13

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter by Yazid, E., Liew, M.S., Parman, S., Kurian, V.J.

    Published 2015
    “…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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  14. 14

    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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    Conference or Workshop Item
  15. 15

    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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    Final Year Project
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    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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  17. 17

    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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    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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  20. 20

    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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