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  1. 1

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

    Published 2012
    “…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 other ant based algorithm, in terms of resource utilization. …”
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    Monograph
  2. 2

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

    Published 2011
    “…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
  3. 3

    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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    Monograph
  4. 4

    Logic Programming In Radial Basis Function Neural Networks by Hamadneh, Nawaf

    Published 2013
    “…I used different types of optimization algorithms to improve the performance of the neural networks. …”
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    Thesis
  5. 5

    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

    Published 2021
    “…Each dataset is set to 10 different problems and the result of the iteration number was as follows: first datasets; new augmentation algorithm = 2, QSM = 4, BLSA = 7, and Simplex = 13 and second datasets; new augmentation algorithm = 1, QSM = 3, BLSA = 4, and Simplex = 8.…”
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    Thesis
  6. 6

    Self-similar network traffic using Random Midpoint Displacement (RMD) algorithm / Jumaliah Saarini by Saarini, Jumaliah

    Published 2006
    “…The way to solve this problem, we applied the existed method in visual C++ programming with used the Random midpoint Displacement (RMD) algorithm. …”
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    Student Project
  7. 7

    Genetic Algorithm for Web Data Mining by Loo, Kevin Teow Aik

    Published 2001
    “…New strains of individuals from a new population were used to test the results obtained from the World Wide Web. …”
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    Project Paper Report
  8. 8

    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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    Thesis
  9. 9

    Reversible circuit synthesis by genetic programming using dynamic gate libraries by Abubakar, M.Y., Jung, L.T., Zakaria, N., Younes, A., Abdel-Aty, A.-H.

    Published 2017
    “…We have defined a new method for automatic construction of reversible logic circuits by using the genetic programming approach. …”
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    Article
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    Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension by Affandy

    Published 2015
    “…Taking into account from those main issues, this study introduces the new model of integrated algorithm-program visualization (ALPROV) for developing program comprehension tool. …”
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    Thesis
  12. 12

    A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch by Mohamad Ridzuan, Mohamad Radzi, Hassan, Elia Erwani, Abdullah, Abdul Rahim, Bahaman, Nazrulazhar, Abdul Kadir, Aida Fazliana

    Published 2016
    “…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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    Article
  13. 13

    Optimize class time tabling by using genetic algorithm technique in UTHM by Ahmad, Izah Rafidah

    Published 2019
    “…In existing research, many problems involving scheduling have been solved by using genetic algorithm method. There are many other methods that were also being used such as linear programming, integer linear programming, tabu search, ant colony optimization (ACO) algorithm and goal programming. …”
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    Thesis
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    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

    Published 2018
    “…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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    Thesis
  17. 17

    Dual-head marking performance optimisation via evolutionary solutions by Koh J., Tiong S.K., Aris I.B., Mahmoud S.

    Published 2023
    “…This paper presents a new approach to optimise the performance of a multi-head marking system in terms of its marking speed This processing method named as MMA (Molecular Marking Optimisation algorithm) will adopt the use of Genetic Algorithm. …”
    Conference paper
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    Chaotic mutation immune evolutionary programming for photovoltaic planning in power system / Sharifah Azma Syed Mustaffa by Syed Mustaffa, Sharifah Azma

    Published 2020
    “…New automatic contingency analysis and ranking algorithm due to line and generator outages were separately developed considering the FVSI value. …”
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    Thesis
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    Automatic marking system for programming subject by Chan, Jin Yee

    Published 2023
    “…This project is a web application designed for lecturer that teaching programming subject to automatically mark programming algorithm exercise. …”
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    Final Year Project / Dissertation / Thesis