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  1. 1
    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
    “…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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  2. 2
    Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy

    Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy by Bhandari, A.K., Singh, V.K, Kumar, A., Singh, G.K.

    Published 2014
    “…To overcome this problem, two successful swarm-intelligence-based global optimization algorithms, cuckoo search (CS) algorithm and wind driven optimization (WDO) for multilevel thresholding using Kapur’s entropy has been employed. …”
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  3. 3
    Ant colony optimization for rule induction with simulated annealing for terms selection

    Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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  4. 4
    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)

    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…Program system assigns user tasks to the suitable Virtual Machines in order to attain Quality of Service (QoS) parameters. Optimization algorithms can be used to solve Non-deterministic Polynomial (NP) hard problem like system management. …”
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    Academic Exercise
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  5. 5
    Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection

    Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

    Published 2026
    “…Conversely, for the PAMAP2 dataset, BDE algorithm displays superior feature selection quality and BPSO algorithm maintains competitive performance and adaptability. …”
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  6. 6
    Development of high quality speech compression system for Quranic recitation based on modified CELP algorithm

    Development of high quality speech compression system for Quranic recitation based on modified CELP algorithm by Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2013
    “…Lastly, we evaluate the performance of the developed algorithm objectively using PESQ (Perceptual Evaluation of Speech Quality). …”
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  7. 7
    Investigation of gateway placement optimization approaches in wireless mesh networks using genetic algorithms

    Investigation of gateway placement optimization approaches in wireless mesh networks using genetic algorithms by M. Ahmed, Awadallah, Hassan Abdalla Hashim, Aisha, Hassan, Wan Haslina

    Published 2014
    “…The investigation result shows that the genetic algorithms based approaches on solving gateway optimization problem relatively outperform many other approaches in addition to that the strength of the genetic algorithm depends on the fitness function which is used in measuring the quality of the individuals (fitness value).…”
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  8. 8
    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…In this study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
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  9. 9
    Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy

    Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

    Published 2023
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  10. 10
    Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh

    Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh by Hisham Ahmad, Theeb Shehadeh

    Published 2018
    “…In this work, Single Objective Optimization Algorithm (SOOA) is proposed. The SOOA version is extended to Multi Objective Optimization Algorithm (MOOA). …”
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  11. 11
    Wind farm reactive power optimization by using imperialist competitive algorithm

    Wind farm reactive power optimization by using imperialist competitive algorithm by Soheilirad, Mohammadsoroush, Hizam, Hashim, Farzan, Payam, Hojabri, Mojgan, Fallah, Seyedeh Narjes, Soheilirad, G.

    Published 2013
    “…In this paper a new evolutionary computing method based on imperialist competitive algorithm (ICA) is used for optimization of the reactive power in a wind farm. …”
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  12. 12
    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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  13. 13
    Metaheuristic nature-inspired algorithms for reservoir optimization operation: A systematic literature review

    Metaheuristic nature-inspired algorithms for reservoir optimization operation: A systematic literature review by Nor Shuhada, Ibrahim, Nafrizuan, Mat Yahya, Saiful Bahri, Mohamed

    Published 2022
    “…Commonly, the metaheuristic optimization algorithm has always been used in hydrology field, especially in reservoir optimization. …”
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  14. 14
    Wind Farm Reactive Power Optimization by Using Imperialist Competitive Algorithm

    Wind Farm Reactive Power Optimization by Using Imperialist Competitive Algorithm by Soheilirad, M., Hizam, H., Farzan, P., Hojabri, Mojgan, Fallah, S. N., Soheilirad, G.

    Published 2013
    “…In this paper a new evolutionary computing method based on imperialist competitive algorithm (ICA) is used for optimization of the reactive power in a wind farm. …”
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  15. 15
    Improved gravitational search algorithm for optimal placement and sizing of distributed generation for power quality enhancement

    Improved gravitational search algorithm for optimal placement and sizing of distributed generation for power quality enhancement by Daud, Sa'adah

    Published 2017
    “…In order to obtain the best compromise solution, a novel heuristic algorithm based on improved gravitational search algorithm (IGSA) is proposed as an optimization technique. …”
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  16. 16
    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems

    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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  17. 17
    Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems

    Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions. …”
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  18. 18
    Optimization of milling parameters using ant colony optimization

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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  19. 19
    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
    “…The proposed fuzzy adaptive teaching learning-based optimization algorithm uses three measures from the search space, namely, quality measure, diversification measure, and intensification measure. …”
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  20. 20
    Path optimization using genetic algorithm in laser scanning system

    Path optimization using genetic algorithm in laser scanning system by Chen, Chai Phing, Koh, Johnny Siaw Paw, Aris, Ishak, Fong, Albert Yu Chooi, Tiong, Sieh Kiong

    Published 2008
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