Search Results - (( evolution optimization bees algorithm ) OR ( colony optimization based algorithm ))

Refine Results
  1. 1

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
    Get full text
    Get full text
    Thesis
  2. 2

    An application of grey wolf optimizer for commodity price forecasting by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Yusof, Yuhanis

    Published 2015
    “…Over the recent decades, there are many nature inspired optimization algorithms have been introduced.In this study, a newly algorithm namely Grey Wolf Optimizer (GWO) is employed for gasoline price forecasting.The performance of GWO is compared against the results produced by Artificial Bee Colony (ABC) algorithm and Differential Evolution (DE) algorithm. …”
    Get full text
    Get full text
    Article
  3. 3

    An Application of Grey Wolf Optimizer for Commodity Price Forecasting by Zuriani, Mustaffa, M. H., Sulaiman, Yuhani, Yusof

    Published 2015
    “…The performance of GWO is compared against the results produced by Artificial Bee Colony (ABC) algorithm and Differential Evolution (DE) algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…The mean closure performance of the BSCCH algorithm is compared against seven selected state-of-the-art algorithms, namely Differential Evolution with Adaptive Trial Vector Generation Strategy and Cluster-replacement-based Feasibility Rule (CACDE), Improved Teaching Learning Based Optimization (ITLBO), Modified Global Best Artificial Bee Colony (MGABC), Stochastic Ranking Differential Evolution (SRDE), Novel Differential Evolution (NDE), Partical Swarm Optimization for solving engineering problems-a new constraint handling mechanism (CVI-PSO) and Ensemble of Constraint Handling Techniques (ECHT). …”
    Get full text
    Get full text
    Article
  5. 5

    Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm by Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Kendall, Graham, Chuah, Joon Huang

    Published 2018
    “…However, the complexity of these processes requires an expert system that involves swarm intelligence-based metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and Differential Evolution (DE) for simulation and optimization of the feeding trajectories. …”
    Get full text
    Get full text
    Article
  6. 6

    Hybridization Of Deterministic And Metaheuristic Approaches In Global Optimization by Goh, Khang Wen

    Published 2019
    “…In the analysis of the literature, Artificial Bees Colony (ABC) Algorithm has been selected as the metaheuristic approach to be improved its capability and efficiency to solve the global optimization problems. …”
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

    A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

    Published 2024
    “…Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
    Get full text
    Get full text
    Article
  9. 9

    Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

    Published 2018
    “…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    Time series forecasting of energy commodity using grey wolf optimizer by Yusof, Yuhanis, Mustaffa, Zuriani

    Published 2015
    “…The ability to model and perform decision making is an essential feature of many real-world applications including the forecasting of commodity prices.In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting.The model is built upon data obtained from the West Texas Intermediate (WTI) crude oil and gasoline price.Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE).Results showed that the GWO model outperformed DE in both crude oil and gasoline price forecasting. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11

    Time Series Forecasting of Energy Commodity using Grey Wolf Optimizer by Zuriani, Mustaffa, Yuhanis, Yusof

    Published 2015
    “…Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE). …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  12. 12

    Coil Optimization using Metaheuristic Techniques for Wireless Charging of Electric Vehicles - A Comparative Analysis. by Imtiaz T., Elsanabary A., Mekhilef S., Mubin M.B., Soon T.K., Aziz N.F.A.

    Published 2024
    “…Differential Evolution (DE), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) optimization algorithms are used to obtain the lengths of all the turns of the transmitter coil. …”
    Conference Paper
  13. 13

    Optimizing large scale combinatorial problems using multiple ant colonies algorithm based on pheromone evaluation technique by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

    Published 2008
    “…The new algorithm is based on the ant colony system and utilizes average and maximum pheromone evaluation mechanisms. …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14
  15. 15

    A new multiple ant colonies optimization algorithm utilizing average pheromone evaluation mechanism by Aljanaby, Alaa, Ku-Mahamud, Ku Ruhana, Md Norwawi, Norita

    Published 2008
    “…Multiple ant colonies optimization is an extension of the Ant Colony Optimization framework It offers a good opportunity to improve the ant colony optimization algorithms by encouraging the exploration of a wide area of the search space without losing the chance of exploiting the history of the search.This paper proposes a new multiple ant colonies optimization algorithm that is based on ant colony system and utilizes ave rage pheromone evaluation mechanism.The new algorithm divides the ants’ populations into multiple ant colonies and can be used to tackle large volume combinatorial optimization problems effectively. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  16. 16

    Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

    Published 2024
    “…This study aims to evaluate the effectiveness of two optimization algorithms, artificial bee colony (ABC) and spiral dynamic algorithm (SDA), in controlling the position of a flexible-link manipulator. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
    Get full text
    Get full text
    Article
  18. 18

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
    Get full text
    Get full text
    Article
  19. 19

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
    Get full text
    Get full text
    Article
  20. 20

    MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

    Published 2023
    “…Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
    Get full text
    Get full text
    Article