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  1. 1

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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    Thesis
  2. 2

    A multiobjective simulated Kalman filter optimization algorithm by A. Azwan, A. Razak, Mohd Falfazli, Mat Jusof, Ahmad Nor Kasruddin, Nasir, Mohd Ashraf, Ahmad

    Published 2018
    “…This paper presents a new multiobjective type optimization algorithm known as a Multiobjective Optimization Simulated Kalman Filter (MOSKF). …”
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    Conference or Workshop Item
  3. 3

    Cubature kalman optimizer : A novel metaheuristic algorithm for solving numerical optimization problems by Zulkifli, Musa, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai, Tsuboi, Yusei

    Published 2023
    “…To further validate the performance, the proposed CKO is compared with well-known algorithms, including single-agent finite impulse response optimizer (SAFIRO), single-solution simulated Kalman filter (ssSKF), simulated Kalman filter (SKF), asynchronous simulated Kalman filter (ASKF), particle swarm optimization algorithm (PSO), genetic algorithm (GA), grey wolf optimization algorithm (GWO), and black hole algorithm (BH). …”
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    Article
  4. 4

    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem by Ismail, Zuhaimy, Nurhadi, Irhamah, Zainuddin, Zaitul Marlizawati

    Published 2008
    “…Simulated Annealing is a global optimization technique which traverses the search space by generating neighboring solutions of the current solution. …”
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    Monograph
  5. 5

    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

    Published 2016
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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    Conference or Workshop Item
  6. 6

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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    Thesis
  7. 7

    Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions by Abdolrasol M.G.M., Jern Ker P., Hannan M.A., Tiong S.K., Ayob A., Almadani J.F.S.

    Published 2024
    “…Real-world energy demand and weather data are integrated for practical relevance. Rigorous simulations within MATLAB/Simulink establish a robust analytical framework, evaluating optimization algorithms and identifying optimal configurations. …”
    Conference Paper
  8. 8

    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems by Zuwairie, Ibrahim, Zulkifli, Md. Yusof, Asrul, Adam, Kamil Zakwan, Mohd Azmi, Tasiransurini, Ab Rahman, Badaruddin, Muhammad, Nor Azlina, Ab. Aziz, Norrima, Mokhtar, Mohd Ibrahim, Shapiai, Mohd Saberi, Mohamad

    Published 2018
    “…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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    Article
  9. 9

    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…Purpose – The purpose of the research is to solve Travelling Salesman Problem (TSP) using Simulated Kalman Filter (SKF) algorithm and single-solution SKF (ssSKF) algorithm based on numerical ordering technique. …”
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    Conference or Workshop Item
  10. 10

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…Majority of the research works in this project were in CAE software environment and method to implement optimization to 1D engine simulation. The paper conducts design optimization of CAMPRO 1.6L (S4PH) engine valve timing at various engine speeds using multi-objective genetic algorithm (MOGA) for the future variable valve timing (VVT) system research and development. …”
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    Proceeding Paper
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  12. 12

    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2018
    “…Furthermore, the obtained results disclose the superiority of the proposed QOMJaya algorithm over both the proposed MJaya algorithm and several previous algorithms in terms of solution optimality and feasibility.…”
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    Article
  13. 13

    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems by Yusof, Zulkifli Md., Ibrahim, Zuwairie, Adam, Asrul, Azmi, Kamil Zakwan Mohd, Ab. Rahman, Tasiransurini, Muhammad, Badaruddin, Ab. Aziz, Nor Azlina, Abd Aziz, Nor Hidayati, Mokhtar, Norrima, Shapiai, Mohd Ibrahim, Muhammad, Mohd Saberi

    Published 2018
    “…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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    Article
  14. 14

    Opposition-based Whale Optimization Algorithm by Alamri, Hammoudeh S., Alsariera, Yazan A., Kamal Z., Zamli

    Published 2018
    “…The Whale Optimization Algorithm (WOA) is a newly proposed metaheuristic optimization algorithm, which simulate humpback whales hunting behavior. …”
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    Article
  15. 15

    Optimal power flow using the Jaya algorithm by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2016
    “…Statistical analysis is also carried out to check the reliability of the Jaya algorithm. The optimal solution obtained by the Jaya algorithm is compared with different stochastic algorithms, and demonstrably outperforms them in terms of solution optimality and solution feasibility, proving its effectiveness and potential. …”
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    Article
  16. 16

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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    Thesis
  17. 17

    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

    Published 2020
    “…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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    Final Year Project
  18. 18

    Simulated kalman filter algorithm with improved accuracy by Mohd Falfazli, Mat Jusof, Ahmad Azwan, Abdul Razak, Shuhairie, Mohammad, Ahmad Nor Kasruddin, Nasir, Mohd Helmi, Suid, Mohd Ashraf, Ahmad, Zuwairie, Ibrahim

    Published 2018
    “…This paper presents an improved Simulated Kalman Filter optimiza-tion algorithm. It is a further enhancement of a Simulated Kalman Filter (SKF) optimization algorithm. …”
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    Book Chapter
  19. 19

    Simulation for dynamic patients scheduling based on many objective optimization and coordinator by Mahmed, Ali Nader, Mohd Nizam, Mohmad Kahar

    Published 2024
    “…Simulator evaluation and comparison between several optimization algorithms show the superiority of NSGA-III in terms of set criticality and soft constraint values. …”
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    Article
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