Search Results - (( (programs OR program) _ minimization algorithm ) OR ( java simulation optimization algorithm ))

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  1. 1

    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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    Thesis
  2. 2

    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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  3. 3

    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…This project present a system program algorithm based on Moth Flame Optimization (MFO) algorithm to assign an optimal set of system program to meet the satisfaction of quality of service requirements of cloud computing in such a way that the total execution time of tasks is minimized. …”
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    Academic Exercise
  4. 4

    An Integer Linear Programming model and Adaptive Genetic Algorithm approach to minimize energy consumption of Cloud computing data centers by Ibrahim, Huda, Aburukba, Raafat O., El-Fakih, Khaled

    Published 2018
    “…Hence, solutions are needed to minimize the energy consumption. This paper focuses on the development of a dynamic task scheduling algorithm by proposing an Integer Linear Programming (ILP) model that minimizes the energy consumption in a Cloud data center. …”
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    Article
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    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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    Article
  7. 7

    Integrated immune-commensal-evolutionary programming for economic dispatch and distributed generation installation / Mohd Helmi Mansor by Mansor, Mohd Helmi

    Published 2020
    “…ICEP is developed from the hybridization of three independent optimization techniques, namely Symbiotic Organisms Search (SOS), Artificial Immune System (AIS) and Evolutionary Programming (EP). EP is the leading optimizer of the hybrid algorithm while cloning operator of AIS and commensal operator of SOS are adopted into the EP algorithm to improve its performance. …”
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  8. 8

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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    Article
  9. 9

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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    Article
  10. 10

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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    Article
  11. 11

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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    Article
  12. 12

    Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

    Published 2023
    “…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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    Article
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    A 16kV distribution network reconfiguration by using evolutionaring programming for loss minimizing by Sulaima, Mohamad Fani, Shidan, Murnie Shakilla, Mohd Dahalan, Wardiah, Mokhlis, Hazlie, Baharom, Mohamad Faizal, Jaafar, Hazriq Izzuan

    Published 2014
    “…Where with the increasing of electricity demand, intelligence algorithm is one of the optimization search engine that may help in minimizing the power losses in the power distribution network. …”
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    Article
  15. 15

    Comparative study of optimal power flow using evolutionary programming and immune evolutionary programming technique in power system / Mohd Khairil Izwan Md Daim by Md Daim, Mohd Khairil Izwan

    Published 2006
    “…The study explores two functions namely total loss minimization and total cost minimization as the objective fimction. …”
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  16. 16

    Control algorithm for two-tank system using multiparametric programming by Zakaria, A., Mid, E.C., Mohamed, M.F., Hussin, M.H.M., Shaari, A.S., Ruslan, Eliyana, Hadi, Dayanasari, Masri, M.

    Published 2023
    “…This study proposes a control algorithm for a two-tank system based on multiparametric programming. …”
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    Conference or Workshop Item
  17. 17

    Application of the genetic algorithm in determining compensating capacitors sizing for loss minimization in power system / Saodah Omar by Omar, Saodah

    Published 2003
    “…This report present the applications of genetic algorithm in determining compensating capacitors sizing for loss minimization in power system. …”
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    Surveillance camera placement optimization using Particle Swarm Optimization (PSO) algorithm and Mixed-Integer Linear Programming (MILP) model / `Ain Safia Roslan by Roslan, `Ain Safia

    Published 2024
    “…This project explores the optimization of surveillance camera placements using Particle Swarm Optimization (PSO) and Mixed-Integer Linear Programming (MILP). PSO, inspired by the social behaviour of birds flocking or fish schooling, is a heuristic algorithm known for its flexibility and exploration capabilities. …”
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