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  1. 1

    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

    Published 2018
    “…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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    Thesis
  2. 2

    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

    Published 2015
    “…However, the result normally faces local optima problems. This situation can be solved by embedding Genetic Algorithm (GA) in the network to replace back-propagation method. …”
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    Thesis
  3. 3

    Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

    Published 2008
    “…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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    Undergraduates Project Papers
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    Normal-boundary intersection based parametric multi-objective optimization of green sand mould system by Ganesan, T., Vasant, P., Elamvazuthi, I.

    Published 2013
    “…In this work, a novel approach that merges meta-heuristic algorithms with the Normal Boundary Intersection (NBI) method is introduced. …”
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    Article
  6. 6

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
    Conference paper
  7. 7

    Adapting the Elitism on the Greedy Algorithm for Variable Strength Combinatorial Test Cases Generation by Bahomaid, Ameen A., Alsewari, Abdulrahman A., Zamli, Kamal Z., Alsariera, Yazan A.

    Published 2018
    “…This study presented the most recent variable interaction strength (VS) CT strategy using an enhanced variant in the greedy algorithm. …”
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    Article
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    Message based random variable length key encryption algorithm. by Mirvaziri, Hamid, Jumari, Kasmiran, Ismail, Mahamod, Mohd Hanapi, Zurina

    Published 2009
    “…In order to overcome analysis mentioned above a new algorithm is designed that is based on random numbers and also can defeat time and memory constraints. …”
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    Article
  11. 11

    Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing by S. Ahmed, Bestoun

    Published 2011
    “…This thesis presents the design and implementation of a new interaction test generation strategy, known as the Particle Swarm-based Test Generator (PSTG), for generating t-way and variable-strength test suites. …”
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    Thesis
  12. 12

    An algorithmic framework for multiobjective optimization by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2013
    “…Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. …”
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    Article
  13. 13

    Scheduling scientific workflow in multi-cloud: a multi-objective minimum weight optimization decision-making approach by Farid, Mazen, Heng, Siong Lim, Chin, Poo Lee, Latip, Rohaya

    Published 2023
    “…A significant number of NP-hard problem optimization methods employ multi-objective algorithms. …”
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    Article
  14. 14

    A variable combinatorial test suite strategy based on modified greedy algorithm by Homaid, Ameen A. Ba, Alsewari, Abdulrahman A.

    Published 2015
    “…This proposed will suggest a new CIT strategy based on a modified greedy algorithm (MGA) with addressing the supporting of variable strength interaction to generate a satisfactory test suite size.…”
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    Conference or Workshop Item
  15. 15

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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    Article
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    Taguchi's method for optimized neural network based autoreclosure in extra high voltage lines by K.S.R., Rao, Z.F., Desta

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with Levenberg Marquardt algorithm to train the ANN and Taguchi's Method to find optimal parameters of the algorithm and number of hidden neurons. …”
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    Conference or Workshop Item
  18. 18

    Adaptive route optimization for mobile robot navigation using evolutionary algorithm by Kit Guan Lim, Guan Lim, Yoong Hean Lee, Hean Lee, Min Keng Tan, Keng Tan, Hou, Pin Yoong, Tienlei, Wang, Tze, Kenneth Kin Teo

    Published 2021
    “…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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    Proceedings
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    Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

    Published 2008
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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    Conference or Workshop Item
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    Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

    Published 2009
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with standard Error Back-Propagation, Levenberg Marquardt Algorithm and Resilient Back-Propagation training algorithms together with Taguchi’s Method. …”
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    Conference or Workshop Item