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  1. 1
    Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach

    Dynamic Economic Dispatch For Large Scale Power Systems: A Lagrangian Relaxation Approach by Ab Ghani, Mohd Ruddin, Hindi, K. S.

    Published 1991
    “…Otherwise, Dantzig-Wolfe decomposition is invoked, using almost all the information generated during subgradient optimization to ensure a speedy conclusion. The computational efficiency of the algorithm renders it suitable for on-line dispatch.…”
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  2. 2
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  3. 3
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…These methods present an effective alternative that treats plants as black-box systems without requiring explicit models. The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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  4. 4
    Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems

    Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems by Umar D.A., Alkawsi G., Jailani N.L.M., Alomari M.A., Baashar Y., Alkahtani A.A., Capretz L.F., Tiong S.K.

    Published 2024
    “…Furtherly, Artificial Intelligence (AI)-based MPPT algorithms were proposed for the WEHS as either standalone or integrated with the traditional MPPT methods. …”
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  5. 5
    Integration of simulation for ergonomics assessment in operation control centre (railway industries) / Adib Zulfadhli Mohd Alias

    Integration of simulation for ergonomics assessment in operation control centre (railway industries) / Adib Zulfadhli Mohd Alias by Adib Zulfadhli, Mohd Alias

    Published 2019
    “…This study will focus on the translation of the CAD/Revit model into simulation software, either directly or through the intermediate stage of rendering package. Complete CAD/Revit model can be used to generate simulation model by straight forward translation of the whole model or with the algorithms for optimization. …”
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  6. 6
    Development of intelligent evaluation system for product end-of-life selection strategy

    Development of intelligent evaluation system for product end-of-life selection strategy by Zakri, Ghazalli

    Published 2011
    “…This study integrates the travelling salesman problem with genetic algorithm (TSP-GA) for finding the optimal disassembly sequence and disassembling the EOL product. …”
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  7. 7
    Intelligent traffic lights using Q-learning

    Intelligent traffic lights using Q-learning by Mohd Yusop, Muhammad Aminuddin, Mansor, Hasmah, Gunawan, Teddy Surya, Nasir, Haidawati,

    Published 2022
    “…Q-learning derives benefits from past experiences and determines the optimal course of action based on them. The performance of the proposed system has been measured against that of the traditional system, which is a fixed time cycle system. …”
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  8. 8
    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals

    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

    Published 2015
    “…The idea of hybridizing the newly developed biogeography based optimization algorithm (BBO) with variable neighborhood structure (VNS) is proposed in order to produce a high performance initial schedule in terms of minimum completion time, tardiness and flow time within reasonable amount of time. …”
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  9. 9
    Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units

    Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units by Peddakapu, K., M. R., Mohamed, M. H., Sulaiman, Srinivasarao, P., Kishore, D. J. K., P. K., Leung

    Published 2021
    “…Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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  10. 10
    Hybrid scheduling and dual queue scheduling

    Hybrid scheduling and dual queue scheduling by Mahmood, Ahmad Kamil

    Published 2009
    “…Our research work involves the design and development of new CPU scheduling algorithms (the Hybrid Scheduling Algorithm and the Dual Queue Scheduling Algorithm) with a view to optimization. …”
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  11. 11
    Hybrid scheduling and dual queue scheduling

    Hybrid scheduling and dual queue scheduling by A., Oxley, S.N.M., Shah, A.K., Mahmood

    Published 2009
    “…Our research work involves the design and development of new CPU scheduling algorithms (the Hybrid Scheduling Algorithm and the Dual Queue Scheduling Algorithm) with a view to optimization. …”
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  12. 12
    Opposition-based Whale Optimization Algorithm

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

    Published 2018
    “…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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  13. 13
    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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  14. 14
    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

    Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem by Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2015
    “…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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  15. 15
    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
    “…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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  16. 16
    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

    An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

    Published 2021
    “…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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  17. 17
    Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network

    Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network by Vincent Chung, Norah Tuah, Kit Guan Lim, Min Keng Tan, Ismail Saad, Kenneth Tze Kin Teo

    Published 2020
    “…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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  18. 18
    Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm

    Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm by Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

    Published 2024
    “…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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  19. 19
    Simulated Kalman Filter algorithms for solving optimization problems

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

    Published 2019
    “…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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  20. 20
    A Multi-State Gravitational Search Algorithm for Combinatorial Optimization Problems

    A Multi-State Gravitational Search Algorithm for Combinatorial Optimization Problems by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2015
    “…The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. …”
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