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  1. 1
    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots

    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
    “…A simulated Khepera robot is evolved by a Pareto-frontier Differential Evolution (POE) algorithm, and learned through a 3-layer feed-forward artificial neural network, attempting to simultaneously fulfill two conflicting objectives of maximizing robot phototaxis behavior while minimizing the neural network's hidden neurons by generating a Pareto optimal set of controllers. …”
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    Research Report
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  2. 2
    Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems

    Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems by Mohd Zakimi, Zakaria, Hishamuddin, Jamaluddin, Robiah, Ahmad, Sayed Mohammad Reza, Loghmanian

    Published 2013
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    Working Paper
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  3. 3
    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)

    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
    “…The GT-Power model is run simultaneously with mode Frontier to perform multi-objective optimization. Multi-objective Genetic Algorithms (MOGA) are an extension of Genetic Algorithms (GA) that does not require multiple objectives to be aggregated to one value. …”
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    Proceeding Paper
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  4. 4
    Multi-Objective Optimal Energy Management of Nanogrid Using Improved Pelican Optimization Algorithm

    Multi-Objective Optimal Energy Management of Nanogrid Using Improved Pelican Optimization Algorithm by Jamal S., Pasupuleti J., Rahmat N.A., Tan N.M.L.

    Published 2025
    “…This strategy, which is based on the improved pelican optimization algorithm (IPOA), involves the development of a multi-objective optimization (MOA) equation with several constraints, while taking into account the Malaysian grid purchasing and selling prices. …”
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  5. 5
    Convergence Analysis of the African Buffalo Optimization Algorithm

    Convergence Analysis of the African Buffalo Optimization Algorithm by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad

    Published 2016
    “…This paper presents the convergence analysis of the newly-developed African Buffalo Optimization algorithm. African Buffalo Optimization is a simulation of the organizational skills of the African buffalos using two basic sounds: /waaa/ and /maaa/ as they transverse the African landscape in search of grazing pastures. …”
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  6. 6
    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems

    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
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  7. 7
    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
    “…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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  8. 8
    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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  9. 9
    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution

    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
    “…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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  10. 10
    Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots

    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
    “…The ANN acts as a controller for radio frequency (RF)-Iocalization behavior of a Khepera robot simulated in a 3D physics-based environment. …”
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    Research Report
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  11. 11
    Application of Multi-objective Genetic Algorithm (MOGA) for design optimization of valve timing at various engine speeds

    Application of Multi-objective Genetic Algorithm (MOGA) for design optimization of valve timing at various engine speeds by Mohiuddin, A. K. M., Rahman, Mohammed Ataur, Haw Shin, Yap

    Published 2011
    “…This paper aims to demonstrate the effectiveness of Multi-Objective Genetic Algorithm Optimization and its practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. …”
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  12. 12
    IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks

    IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

    Published 2024
    “…Additionally, simulation results confirm that the proposed algorithm IWDSA exhibits outstanding performance compared to other algorithms utilizing optimization techniques, including genetic algorithms, bat algorithms, ant colony optimization, and swarm optimization. …”
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  13. 13
    Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm

    Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm by Tan K.M., Ramachandaramurthy V.K., Yong J.Y.

    Published 2023
    “…Algorithms; Charging (batteries); Curve fitting; Electric load flow; Electric power systems; Electric vehicles; Energy management systems; Optimization; Reactive power; Real time control; Scheduling; Vehicles; Voltage control; Voltage regulators; Battery chargers; Bidirectional power flow; Multi objective algorithm; Optimization algorithms; Reactive power compensation; Real-time implementations; Revolutionary technology; Vehicle to grids; Electric power transmission networks; algorithm; electric vehicle; electricity supply; energy flow; energy planning; energy use; optimization; technological development…”
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  14. 14
    A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation

    A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation by Rong, Li, Shari, Zalina, Ab Kadir, Mohd Zainal Abidin

    Published 2025
    “…This study systematically examined recent research trends in multi-objective optimization (MOO) for building performance from 2020 to 2024 and proposed a conceptual framework integrating intelligent algorithms, simulation tools, and climate adaptation strategies. …”
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  15. 15
    A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega)

    A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega) by Tan, Tun Tai

    Published 2009
    “…Simulation runs on GAs and VEGA are developed to demonstrate their capability in solving optimization problems. …”
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    Final Year Project Report / IMRAD
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  16. 16
    A Fuzzy Hybrid GA-PSO Algorithm for Multi-Objective AGV Scheduling in FMS

    A Fuzzy Hybrid GA-PSO Algorithm for Multi-Objective AGV Scheduling in FMS by Mousavi, M., Yap, Hwa Jen, Musa, S.N., Md Dawal, Siti Zawiah

    Published 2017
    “…A fuzzy hybrid GA-PSO (genetic algorithm – particle swarm optimization) algorithm was developed to optimize the model. …”
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  17. 17
    Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index

    Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index by Verayiah R., Mohamed A., Shareef H., Abidin I.H.Z.

    Published 2023
    Conference Paper
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  18. 18
    Development of heuristic methods based on genetic algorithm (GA) for solving vehicle routing problem

    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
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  19. 19
    Long term energy demand forecasting based on hybrid, optimization: Comparative study

    Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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  20. 20
    An evaluation of network load balancing through Ant Colony Optimization (ACO) based technique / Muhammad Nur Zikri Mohamad Hafizan

    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
    “…This project works on developing an efficient network load balancing mechanism based on the Ant Colony Optimization (ACO) algorithm. …”
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    Student Project
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