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  1. 1
    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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  2. 2
    Efficient transmission based on genetic evolutionary algorithm

    Efficient transmission based on genetic evolutionary algorithm by Jin Fan, Kit Guan Lim, Helen Sin Ee Chuo, Min Keng Tan, Ali Farzamnia, Kenneth Tze Kin Teo

    Published 2022
    “…Through the simulation of the transmission performance of genetic optimization algorithm, the comparison of transmission energy consumption between GA and evolutionary algorithm is analyzed, and the evolutionary algorithm with higher transmission performance is obtained. …”
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    Proceedings
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  3. 3
    Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building

    Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2023
    “…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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  4. 4
    Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm

    Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm by Zainol Abidin H., Din N.M., Yassin I.M., Omar H.A., Radzi N.A.M., Sadon S.K.

    Published 2023
    “…A simulation study has been carried out to compare the performance of the proposed algorithm with the multi-objective evolutionary algorithm with fuzzy dominance-based decomposition and an integer linear programming algorithm. …”
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  5. 5
    WSN sensor node placement approach based on multi-objective optimization

    WSN sensor node placement approach based on multi-objective optimization by Abidin H.Z., Din N.M., Radzi N.A.M.

    Published 2023
    “…A sensor node placement algorithm that utilizes Multi-objective Territorial Predator Scent Marking Algorithm (MOTPSMA) is presented in this paper. …”
    Conference Paper
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  6. 6
    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems

    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems by Tan, Joe Yee

    Published 2022
    “…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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  7. 7
    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm

    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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  8. 8
    Simulated Kalman Filter algorithms for solving optimization problems

    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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  9. 9
    Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems

    Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems by Zulkifli, Md. Yusof, Zuwairie, Ibrahim, Ismail, Ibrahim, Kamil Zakwan, Mohd Azmi, Nor Azlina, Ab. Aziz, Nor Hidayati, Abd. Aziz, Mohd Saberi, Mohamad

    Published 2016
    “…Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF). …”
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  10. 10
    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation

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

    Published 2022
    “…The proposed algorithm is simulated for simultaneous OPF-based conflicting objectives, respectively. …”
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  11. 11
    Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms

    Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms by Teo, Jason Tze Wi, Johnny Koh, Chin, Kim On, Chua, Bih Lii, Willey Liew, Noor Ajian Mohd. Lair, Lim, Shun Hoe

    Published 2012
    “…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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    Research Report
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  12. 12
    Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm

    Predictive-reactive job shop scheduling for flexible production systems with the combination of optimization and simulation based algorithm by Abdul Rahman, Azrul Azwan, Joe Yee, Tan, A Rahman, Muhamad Arfauz, Salleh, Mohd Rizal, Bilge, Pinar

    Published 2020
    “…This research will address some aspects of combining simulation and optimization-based algorithms for job-shop scheduling and rescheduling of flexible production systems. …”
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  13. 13
    Opposition-based learning simulated kalman filter for Numerical optimization problems

    Opposition-based learning simulated kalman filter for Numerical optimization problems by Mohd Falfazli, Mat Jusof

    Published 2016
    “…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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    Research Book Profile
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  14. 14
    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application

    A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

    Published 2011
    “…Present paper intends to provide a detailed description of a new bio-inspired Metaheuristic Algorithm. Based on the detailed study of the Drosophila, the flowchart behaviour for the algorithm, code implementation, methodologies and simulation analysis, a novel Fly Optimization Algorithm (FOA) approach is presented. …”
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  15. 15
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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    Undergraduates Project Papers
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  16. 16
    Opposition- based simulated kalman filters and their application in system identification

    Opposition- based simulated kalman filters and their application in system identification by Kamil Zakwan, Mohd Azmi

    Published 2017
    “…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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  17. 17
    The Hybrid of WOABAT-IFDO Optimization Algorithm and Its Application in Crowd Evacuation Simulation

    The Hybrid of WOABAT-IFDO Optimization Algorithm and Its Application in Crowd Evacuation Simulation by Hamizan, Sharbini, Roselina, Sallehuddin, Habibollah, Haron

    Published 2023
    “…This paper proposes a new hybrid of nature inspired optimization algorithm (IFDO-WOABAT) based on the latest optimization algorithm namely Improved Fitness Dependent Optimization (IFDO) with Whale-Bat Optimization algorithm (WOABAT). …”
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    Proceeding
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  18. 18
    Multi-State Particle Swarm Optimization for Discrete Combinatorial Optimization Problem

    Multi-State Particle Swarm Optimization for Discrete Combinatorial Optimization Problem by Ismail, Ibrahim, Hamzah, Ahmad, Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Kamal, Khalil, Muhammad Arif, Abdul Rahim

    Published 2014
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  19. 19
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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  20. 20
    A multiobjective simulated Kalman filter optimization algorithm

    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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