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  1. 1
    Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms

    Development Of Artificial Bee Colony (Abc) Variants And Memetic Optimization Algorithms by Sulaiman, Noorazliza

    Published 2017
    “…The modified ABC variants have been developed by inserting new processing stages into the standard ABC algorithm and modifying the employed-bees and onlooker-bees phases to balance out the exploration and exploitation capabilities of the algorithm. …”
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  2. 2
    Assembly sequence optimization using the bees algorithm

    Assembly sequence optimization using the bees algorithm by Kamaruddin, Shafie, Azmi, Nabilah, Sukindar, Nor Aiman

    Published 2022
    “…It is shown that, the Bees Algorithm obtained similar optimum fitness value with other algorithms but with the greatest number of optimal assembly sequences. …”
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    Book Chapter
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  3. 3
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  4. 4
    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
    “…From the simulation findings, the proposed QGGABC-FFNN outperformed compared with other typical computational algorithms for prediction of SSM values.…”
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  5. 5
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  6. 6
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
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  7. 7
    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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  8. 8
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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  9. 9
    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction

    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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  10. 10
    Artificial bee colony in optimizing process parameters of surface roughness in end milling and abrasive waterjet machining

    Artificial bee colony in optimizing process parameters of surface roughness in end milling and abrasive waterjet machining by Norfadzlan, Bin Yusup

    Published 2012
    “…Optimizing the process parameters is essential in order to provide a better quality and economics machining. This research develops an optimization algorithm using artificial bee colony (ABC) algorithm to optimize the process parameters that will lead to minimum surface roughness (Ra) value for both end miling and abrasive waterjet machining. …”
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    Final Year Project Report / IMRAD
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  11. 11
    Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation

    Adopting Bees Algorithm for Sequenced Based T-Way Test Data Generation by Kamal Z., Zamli, Mohd Hazli, Mohammed Zabil

    Published 2013
    “…Using combinatorial method, our strategy adopted Bees Algorithm (BA) to generate the test data for sequence t-way. …”
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  12. 12
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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  13. 13
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  14. 14
    Resource management in grid computing using ant colony optimization

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
    “…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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  15. 15
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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  16. 16
    Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed

    Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed by Mudasir , Ahmed

    Published 2019
    “…Simulation results show that, at the high-level inverter, the proposed algorithm can easily find the feasible solutions, however, GA, PSO, bee algorithm (BA), and differential evolution (DE) face the difficulty due to less exploration capability. …”
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  17. 17
    Predicting usage for a marketable e-learning portal

    Predicting usage for a marketable e-learning portal by Yaacob, Aizan, Yusof, Yuhanis, Sheik Osman, Wan Rozaini, Derashid, Chek, Omar Khan, Zainizad

    Published 2014
    “…To date, existing e-learning portals focuses on providing various learning materials via online.Such an approach may provide huge benefit to the learners; nevertheless, less value can be obtained by the developers or owners.The knowledge transfer programme provides an insight on how existing e-learning portal can be upgraded.The academia has introduced the industry to a computational modelling that is built upon the behaviour of nature community (i.e bees)The utilization of Artificial Bee Colony algorithm in predicting learners' usage of an e-learning portal provides an indicator to the developers on the portals effectiveness.Such information is then useful in producing a marketable and valuable e-learning portal…”
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    Conference or Workshop Item
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  18. 18
    Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP)

    Development of Guided Artificial Bee Colony (GABC) Heuristic for Permutation Flowshop Scheduling Problem (PFSP) by Sidek, Noor Azizah, Bareduan, Salleh Ahmad, Nawawi, Azli, Jia Yee, Ten

    Published 2024
    “…By adopting a modified version of the Artificial Bee Colony (ABC) algorithm, which has the disadvantage of a slow converge speed, this study aims to boost NEH. …”
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  19. 19
    The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm

    The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm by Nurul Aimi Munirah, ., Muhammad Akmal, Remli, Noorlin, Mohd Ali, Hui, Wen Nies, Mohd Saberi, Mohamad, Khairul Nizar Syazwan, Wan Salihin Wong

    Published 2020
    “…The proposed algorithm has been compared with the other three famous algorithms, which are Particle Swarm Optimization (PSO), Differential Evolutionary (DE), and Bees Optimization Algorithm (BOA). …”
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  20. 20
    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain

    Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

    Published 2020
    “…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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