Search Results - (( sequence optimization based algorithm ) OR ( simulation optimization task algorithm ))

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  1. 1

    Development of Simulated Annealing Based Scheduling Algorithm for Two Machines Flow Shop Problem by M., Muziana, Kamal Z., Zamli

    Published 2015
    “…Viewing as optimization problem and focusing on two machines, this research aims to develop a new Simulated Annealing based scheduling algorithm, called SA2M, for flow shop problem. …”
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    Conference or Workshop Item
  2. 2

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

    Published 2008
    “…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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    Thesis
  3. 3

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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    Thesis
  4. 4

    Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

    Published 2023
    “…The optimal schedules obtained were compared with the actual based on parameters and judgement from power plant planning team. …”
    text::Thesis
  5. 5

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…To improve the performance of the swap sequence based PSO, this paper introduces an Enhanced Swap Sequence based PSO (Enhanced SSPSO) algorithm by integrating the strategies of the Expanded PSO (XPSO) in the swap sequence based PSO. …”
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    Article
  6. 6

    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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    Academic Exercise
  7. 7

    Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application by Hardhienata, Medria Kusuma Dewi, Priandana, Karlisa, Putra, Daffa Rangga, Sriatun, Mamiek, Wulandari, Buono, Agus, Mohamed, Raihani

    Published 2024
    “…Simulation results showed that the proposed ACO algorithm with the modified efficiency factor improved the performance of basic ACO algorithm for solving task allocation problem in terms of the average total travel cost for each agent. …”
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    Article
  8. 8

    OTS: an optimal tasks scheduling algorithm based on QoS in cloud computing network by Alhakimi, Mohammed Ameen, Latip, Rohaya

    Published 2019
    “…This study presents an optimal tasks scheduling algorithm by enhancing Max-Min algorithm. …”
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    Article
  9. 9

    Task scheduling in cloud computing using Harris-Hawk Optimization by Iza A. A. Bahar, Azali Saudi, Abdul Kadir, Syed Nasirin Syed Zainol Abidin, Tamrin Amboala, Esmadi Abu Bin Abu, Abdullah B. Mohd. Tahir, Suddin Lada

    Published 2024
    “…This paper presents a simulation of the Harris-Hawk Optimization (HHO) algorithm, which aims to minimize the makes pan of a specified task set in a cloud computing environment. …”
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    Proceedings
  10. 10

    Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators by Abed I.A., Sahari K.S.M., Koh S.P., Tiong S.K., Jagadeesh P.

    Published 2023
    “…A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. …”
    Conference paper
  11. 11

    An evaluation of network load balancing through Ant Colony Optimization (ACO) based technique / Muhammad Nur Zikri Mohamad Hafizan by Mohamad Hafizan, Muhammad Nur Zikri

    Published 2020
    “…The results also show that the ACO algorithm was able to outperform the Randomized and Round Robin algorithm in all simulation configurations.…”
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    Student Project
  12. 12
  13. 13

    Hybrid Cat Swarm Optimization and Simulated Annealing for Dynamic Task Scheduling on Cloud Computing Environment by Gabi, Danlami, Ismail, Abdul Samad, Zainal, Anazida, Zakaria, Zalmiyah, Al-Khasawneh, Ahmad

    Published 2018
    “…In this study, a Cloud Scalable Multi-Objective Cat Swarm Optimization-based Simulated Annealing algorithm is proposed. …”
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    Article
  14. 14

    An optimal tasks scheduling algorithm based on QoS in cloud computing network by Alhakimi, Mohammed Ameen Mohammed Abdo

    Published 2017
    “…This study presents an optimal task scheduling algorithm by enhancing Max-Min and TS algorithm. …”
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    Thesis
  15. 15

    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

    Published 2006
    “…This research explores a new approach of using a multi-objective evolutionary algorithm (MOEA) to evolve robot controllers in performing phototaxis tasks while avoiding obstacles in a simulated 30 physics environment, to overcome problems involving more than one objective, where these objectives usually trade-off among each other and are expressed in different units. …”
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    Research Report
  16. 16

    Product assembly and disassembly sequence optimization based on genetic algorithm and design for assembly methodologies by Yasin, Azman, Puteh, Nurnasran, Daud, Ruslizam

    Published 2009
    “…In this paper, an Artificial Intelligence (AI) technique, namely Genetic Algorithm (GA) is proposed to optimize product components assembly and disassembly sequences.The proposed methodology is developed and tested on an industrial product made of plastics with no integrated assembly and permanent joint parts.GA method is applied to determine the accuracy and optimum results based on 20 assembly and disassembly sequence solutions that was generated by the Design for Assembly methodology.The results indicated that GA based approach is able to obtain a near optimal solution for assembly and disassembly sequences.…”
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    Conference or Workshop Item
  17. 17

    An enhanced discrete symbiotic organism search algorithm for optimal task scheduling in the cloud by Sa’ad, Suleiman, Muhammed, Abdullah, Abdullahi, Mohammed, Abdullah, Azizol, Ayob, Fahrul Hakim

    Published 2021
    “…Therefore, in this paper, we propose a metaheuristic enhanced discrete symbiotic organism search (eDSOS) algorithm for optimal task scheduling in the cloud computing setting. …”
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    Article
  18. 18

    A filtering algorithm for efficient retrieving of DNA sequence by Abdul Rahman, Mohd Nordin, Mohd. Saman, Md. Yazid, Ahmad, Aziz, Md. Tap, Abu Osman

    Published 2009
    “…The algorithm filtered the expected irrelevant DNA sequences in database from being computed for dynamic programming based optimal alignment process. …”
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    Article
  19. 19

    Product assembly sequence optimization based on genetic algorithm by Yasin, Azman, Puteh, Nurnasran, Daud, Ruslizam, Omar, Mazni, Syed-Abdullah, Sharifah Lailee

    Published 2010
    “…Genetic algorithm (GA) is a search technique used in computing to find approximate solution to optimization and search problem based on the theory of natural selection. …”
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    Article
  20. 20

    Multi-objective grey wolf optimizer algorithm for task scheduling in cloud-fog computing by Saif, Faten A., Latip, Rohaya, Hanapi, Zurina Mohd, Shafinah, Kamarudin

    Published 2023
    “…The simulation result verifies the effectiveness of the MGWO algorithm compared to the state-of-the-art algorithms in reducing delay and Energy consumption.…”
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    Article