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  1. 1
    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment

    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    Published 2016
    “…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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  2. 2
    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks

    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks by Kousha, Mohammad

    Published 2014
    “…COMP techniques are divided into Coordinated Scheduling / Beamforming and Joint Processing. This thesis focuses on downlink joint processing, where each user receives data from various transmission points, improving the signal strength and cancelling interference. …”
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  3. 3
    Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking

    Development of an improved GWO algorithm for solving optimal paths in complex vertical farms with multi-robot multi-tasking by Shen, Jiazheng, Hong, Tang Sai, Fan, Luxin, Zhao, Ruixin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

    Published 2024
    “…The EPDE-GWO algorithm is compared with Genetic Algorithm (GA), Simulated Annealing (SA), Dung Beetle Optimizer (DBO), and Particle Swarm Optimization (PSO). …”
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  4. 4
    Path optimization using genetic algorithm evolution

    Path optimization using genetic algorithm evolution by Low C.Y., Chong K.H., Salleh K., Johnny K.S.P.

    Published 2023
    Conference paper
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  5. 5
    Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim

    Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

    Published 2007
    “…Roadways and telephone systems are the examples of them. Genetic Algorithms (GA), pioneered by John Holland, applies the principle of evolution found in nature to the problem of finding an optimal solution. …”
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  6. 6
    Differential evolution optimization for constrained routing in Wireless Mesh Networks

    Differential evolution optimization for constrained routing in Wireless Mesh Networks by Sanni, Mistura Laide, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina, Ahmed, Gharib Subhi Mahmoud, Anwar, Farhat, Zakaria, Omar

    Published 2014
    “…This solution addresses efficient and optimal routing path construction for cost and quality metrics of the application. …”
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  7. 7
    Literature Review of Optimization Techniques for Chatter Suppression In Machining

    Literature Review of Optimization Techniques for Chatter Suppression In Machining by A. R., Yusoff, Mohamed Reza Zalani, Mohamed Suffian, Mohd Yusof, Taib

    Published 2011
    “…Various algorithms can be applied in the optimization of machining problems; however, Differential Evolution is the most appropriate for use in chatter suppression, being less time consuming, locally optimal, and more robust than both Genetic Algorithms, despite their wide applications, and Sequential Quadratic Programming, which is a famous conventional algorithm.…”
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  8. 8
    Development of heuristic task scheduling algorithm in cloud computing

    Development of heuristic task scheduling algorithm in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke

    Published 2016
    “…To this direction, in this paper we make a summary of some scheduling algorithms and propose an Enhanced Greedy Heuristic Scheduling Algorithm (EGHSA) for task scheduling adapted for big data applications. …”
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  9. 9
    AGENT MEETING SCHEDULER

    AGENT MEETING SCHEDULER by ZAINAL ABIDIN, NURAINI

    Published 2011
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    Final Year Project
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  10. 10
    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators

    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

    Published 2024
    “…By integrating the ABC algorithm into the manipulator's control system, the goal is to enhance its ability to plan paths and optimize trajectories. …”
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  11. 11
    Two objectives big data task scheduling using swarm intelligence in cloud computing

    Two objectives big data task scheduling using swarm intelligence in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke, Islam, Shayla, Zarir, Abdullah Ahmad

    Published 2016
    “…However, these scheduling algorithms vary in term of their performance and most of these traditional and simple scheduling algorithms may not be efficient for large scale data. …”
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  12. 12
    Simulated annealing algorithm for scheduling divisible load in large scale data grids.

    Simulated annealing algorithm for scheduling divisible load in large scale data grids. by Abdullah, Monir, Othman, Mohamad, Ibrahim, Hamidah, Subramaniam, Shamala

    Published 2009
    “…This paper proposes a novel Simulated Annealing (SA) algorithm for scheduling divisible load in large scale data grids. …”
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  13. 13
    Improved genetic algorithm for scheduling divisible data grid application

    Improved genetic algorithm for scheduling divisible data grid application by Kaid, Monir Abdullah Abduh, Othman, Mohamed, Ibrahim, Hamidah, K. Subramaniam, Shamala

    Published 2007
    “…In this paper, we exploit this property and propose an Improved Genetic Algorithm (IGA) for scheduling divisible data grid applications. …”
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  14. 14
    Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem

    Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem by Ibrahim Abaker , Targio Hashem

    Published 2017
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  15. 15
    Simulated annealing algorithm for scheduling divisible load in large scale data grids

    Simulated annealing algorithm for scheduling divisible load in large scale data grids by Abdullah, Monir, Othman, Mohamed, Ibrahim, Hamidah, K. Subramaniam, Shamala

    Published 2008
    “…This paper proposes a novel simulated annealing (SA) algorithm for scheduling divisible load in large scale data grids. …”
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  16. 16
    MapReduce scheduling algorithms: a review

    MapReduce scheduling algorithms: a review by Hashem, Ibrahim Abaker Targio, Nor Badrul, Anuar, Marjani, Mohsen, Ahmed, Ejaz, Chiroma, Haruna, Ahmad Firdaus, Zainal Abidin, Muhamad Taufik, Abdullah, Faiz, Alotaibi, Mahmoud Ali, Waleed Kamaleldin, Yaqoob, Ibrar, Abdullah, Gani

    Published 2020
    “…Scheduling plays an important role in big data, mainly in reducing the execution time and cost of processing. …”
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  17. 17
    MapReduce scheduling algorithms: a review

    MapReduce scheduling algorithms: a review by Hashem, Ibrahim Abaker Targio, Anuar, Nor Badrul, Marjani, Mohsen, Ahmed, Ejaz, Chiroma, Haruna, Firdaus, Ahmad, Abdullah, Muhamad Taufik, Alotaibi, Faiz, Mahmoud Ali, Waleed Kamaleldin, Yaqoob, Ibrar, Gani, Abdullah

    Published 2018
    “…Scheduling plays an important role in big data, mainly in reducing the execution time and cost of processing. …”
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  18. 18
    A novel scheduling algorithm based on game theory and multicriteria decision making in LTE network

    A novel scheduling algorithm based on game theory and multicriteria decision making in LTE network by Hindia, M.N., Reza, A.W., Noordin, K.A.

    Published 2015
    “…The novel algorithm has proven to be an effective scheduling technique for smart grid applications.…”
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  19. 19
    Enhancement of Ant System Algorithm for Course Timetabling Problem

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
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  20. 20
    Survey on job scheduling mechanisms in grid environment

    Survey on job scheduling mechanisms in grid environment by S. M., Argungu, Che Mohamed Arif, Ahmad Suki, Omar, Mohd Hasbullah

    Published 2015
    “…Grid systems provide geographically distributed resources for both computational intensive and data-intensive applications.These applications generate large data sets.However, the high latency imposed by the underlying technologies; upon which the grid system is built (such as the Internet and WWW), induced impediment in the effective access to such huge and widely distributed data.To minimize this impediment, jobs need to be scheduled across grid environments to achieve efficient data access.Scheduling multiple data requests submitted by grid users onto the grid environment is NP-hard.Thus, there is no best scheduling algorithm that cuts across all grids computing environments.Job scheduling is one of the key research area in grid computing.In the recent past many researchers have proposed different mechanisms to help scheduling of user jobs in grid systems.Some characteristic features of the grid components; such as machines types and nature of jobs at hand means that a choice needs to be made for an appropriate scheduling algorithm to march a given grid environment.The aim of scheduling is to achieve maximum possible system throughput and to match the application needs with the available computing resources.This paper is motivated by the need to explore the various job scheduling techniques alongside their area of implementation.The paper will systematically analyze the strengths and weaknesses of some selected approaches in the area of grid jobs scheduling.This helps researchers better understand the concept of scheduling, and can contribute in developing more efficient and practical scheduling algorithms.This will also benefit interested researchers to carry out further work in this dynamic research area.…”
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