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  1. 1
    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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  2. 2
    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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  3. 3
    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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  4. 4
    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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  5. 5
    AN ENSEMBLE APPROACH OF METAHEURISTIC ALGORITHMS WITH PARABOLIC APPROXIMATION TO OPTIMIZE WELL PLACEMENT PROBLEM

    AN ENSEMBLE APPROACH OF METAHEURISTIC ALGORITHMS WITH PARABOLIC APPROXIMATION TO OPTIMIZE WELL PLACEMENT PROBLEM by ISLAM, JAHEDUL

    Published 2021
    “…However, the ensemble algorithm often changes search strategies and adds an algorithm based on their success, which makes it more reliable on multimodal optimization problems. …”
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  6. 6
    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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  7. 7
    Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm

    Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm by Ling, Kuok Fong, Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

    Published 2023
    “…This research assesses the suitability of the Archimedes Optimization Algorithm (AOA) as a metaheuristic technique to fine-tune a PID controller in a closed-loop DC-DC buck converter. …”
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  8. 8
    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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  9. 9
    CAD Automation Module Based On Cell Moving Algorithm For Incremental Placement Timing Optimization

    CAD Automation Module Based On Cell Moving Algorithm For Incremental Placement Timing Optimization by Kan, Mei War

    Published 2012
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  10. 10
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In the past, many scheduling algorithms were proposed. However, when these techniques were implemented in dense networks, they often lacked the scalability factor due to node failure and dynamic topology changes. …”
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  11. 11
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In the past, many scheduling algorithms were proposed. However, when these techniques were implemented in dense networks, they often lacked the scalability factor due to node failure and dynamic topology changes. …”
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  12. 12
    Distributive and self-sustainable scheduling algorithm for wireless sensor networks

    Distributive and self-sustainable scheduling algorithm for wireless sensor networks by Sheikh, M.A., Ali, N.B.Z., Awang, A.

    Published 2013
    “…In the past, many scheduling algorithms were proposed. However, when these techniques were implemented in dense networks, they often lacked the scalability factor due to node failure and dynamic topology changes. …”
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  13. 13
    A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique

    A Multi-objective Evolutionary Algorithm Based On Decomposition For Continuous Optimization Using A Step-function Technique by Chuah, How Siang

    Published 2022
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  14. 14
    Hybrid of firefly algorithm and pattern search for solving optimization problems

    Hybrid of firefly algorithm and pattern search for solving optimization problems by Wahid, Fazli, Ghazali, Rozaida

    Published 2018
    “…Firefly algorithm (FA) is a newly introduced meta-heuristic, nature-inspired, stochastic algorithm for solving various types of optimization problems. …”
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  15. 15
    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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  16. 16
    Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system

    Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system by Ali, Hazem I.

    Published 2010
    “…These algorithms are designed to achieve the robustness over a wide range of system parameters change and disturbances. …”
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  17. 17
    Search engine optimization techniques for Malaysian university websites a comparative analysis on Google and Bing search engine

    Search engine optimization techniques for Malaysian university websites a comparative analysis on Google and Bing search engine by Shahzad, Asim, Mohd Nawi, Nazri, Sutoyo, Edi, Naeem, Muhammad, Ullah, Arif, Naqeeb, Sundas, Aamir, Muhammad

    Published 2018
    “…As Google modify its algorithm about 500 or more times per year, the web design and internet also evolves dynamically because of changes in SEO techniques and algorithms. …”
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  18. 18
    Ant colony optimization in dynamic environments

    Ant colony optimization in dynamic environments by Chen, Fei Huang

    Published 2010
    “…Dynamic optimization problems differ from the static ones where the optimal solution is dynamic and changes over time. …”
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  19. 19
    Particle swarm optimization for NARX structure selection application on DC motor model: article / Mohd I. Abdullah

    Particle swarm optimization for NARX structure selection application on DC motor model: article / Mohd I. Abdullah by Abdullah, Mohd I.

    “…The BPSO algorithm is an evolutionary computing technique put forward by (Kennedy and Eberhart, 1997). …”
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  20. 20
    Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm

    Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm by M. H., Sulaiman, Muhammad Ikram, Mohd Rashid, Omar, Aliman, Mohd Rusllim, Mohamed, Abu Zaharin, Ahmad, Mohd. Shafie, Bakar

    Published 2014
    “…This paper presents a Swarm Intelligence (SI) technique namely Cuckoo Search Algorithm (CSA) which is inspired by parasitic behaviour of Cuckoo birds in reproduction strategy to obtain loss minimisation by solving the Optimal Reactive Power Dispatch (ORPD) problem. …”
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