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  1. 1

    Design and development of optimal path trace back using graph theory technique for accelerate DNA sequence alignment accelerator: article by Othman, Nor Shuhaida

    Published 2010
    “…The Smith-Waterman is been simplified into four modules which were initialization, score calculation, matrix filling and optimal path. …”
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    Article
  2. 2

    A novel fly optimization algorithm for swarming application by Zainal Abidin, Zulkifli, Ngah, Umi Kalthum, Arshad, Mohd Rizal, Ong, Boon Ping

    Published 2010
    “…This paper presents an initial development stage of Fly Optimization Algorithm which will be used for the path planning system of a swarm of autonomous surface vehicles. …”
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    Proceeding Paper
  3. 3

    Design and development of optimal path trace back using graph theory technique for accelerate DNA sequence alignment accelerator by Othman, Nor Shuhaida

    Published 2010
    “…The Smith-Waterman is been simplified into four modules which were initialization, score calculation, matrix filling and optimal path. …”
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    Student Project
  4. 4

    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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    Article
  5. 5
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    Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

    Published 2020
    “…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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    Thesis
  7. 7

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…In the fourth phase, the newly developed algorithm undergoes testing on the formulated ROOPs and compared to several contemporary optimizer algorithms. …”
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    Thesis
  8. 8

    Artificial neural networks based optimization techniques: A review by Abdolrasol M.G.M., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Hannan M.A., Mohamed R., Ali J.A., Mekhilef S., Milad A.

    Published 2023
    “…In the last few years, intensive research has been done to enhance artificial intelligence (AI) using optimization techniques. In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”
    Review
  9. 9

    Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

    Published 2021
    “…Initially, PSO algorithm was adapted to find the globally optimal result based on unorganized particle movement in the search space toward the optimal solution. …”
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    Thesis
  10. 10
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    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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    Monograph
  12. 12

    Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm by Ariff Nijay, Ramli

    Published 2023
    “…Then, the TTA is developed before undergoing functionality tests by benchmarking with Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA). …”
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    Thesis
  13. 13
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    Parametric Optimization for the Maximization of Hydrogen Production by Enterobacter Cloacae by Saidin, Mohamad Shakir Amri

    Published 2015
    “…A comparison between these three algorithms used is done to compare the optimization results and discuss their advantages and disadvantages.…”
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    Final Year Project
  15. 15

    Hybrid artificial immune system-genetic algorithm optimization based on mathematical test functions by Ali M.O., Koh S.P., Chong K.H., Yap D.F.W.

    Published 2023
    “…Secondly, a Genetic Algorithm is typically initializing population randomly. …”
    Conference paper
  16. 16

    Optimized processing of satellite signal via evolutionary search algorithm by Hassan, Azmi, Othman, Rusli, Tang, Kieh Ming

    Published 2000
    “…This will take away the constraint resulted from the AS policy in processing the GPS satellites signal. The algorithm also shows its robustness because it does not require a good initial starting point. …”
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    Article
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    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
  19. 19

    Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method by Ramachandran, Murugan, Sundaram, Arunachalam, Ridha, Hussein Mohammed, Mirjalili, Seyedali

    Published 2024
    “…The existing literature extensively explores the utilization of powerful Metaheuristic Algorithms (MAs) to address the complex constrained optimization problem in PV systems and achieve optimal solutions. …”
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    Article
  20. 20

    Development of an improved Jellyfish Search (JS) algorithm for solving the optimal path problem of multi-robot collaborative multi-tasking in complex vertical farms by Shen, Jiazheng, Tang, Saihong, Zhao, Ruixin, Fan, Luxin, Mohd Ariffin, Mohd Khairol Anuar, As’arry, Azizan

    Published 2025
    “…Comparative experiments demonstrate that TLDW-JS outperforms classic optimization algorithms such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Dung Beetle Optimization (DBO), achieving superior path length optimization, reduced energy consumption, and improved convergence speed. …”
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    Article