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  1. 1
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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  2. 2
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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  3. 3
    Multi-objective optimisation of assembly line balancing type-e problem with resource constraints

    Multi-objective optimisation of assembly line balancing type-e problem with resource constraints by Masitah, Jusop

    Published 2016
    “…In the second phase of this research, an algorithm will be developed to optimise the problem. …”
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  4. 4
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…In conclusion, a deep reinforcement learning algorithm was successfully developed for the substrate feeding rate optimisation in the fed-batch baker’s yeast fermentation process. …”
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  5. 5
    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…The first modification enhances the initial population of the MBGWO using a heuristic based Ant Colony Optimisation algorithm. The second modification develops a new position update mechanism using the Bat Algorithm movement. …”
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  6. 6
    Develpoment of combinatorial optimisation for cutting tool path strategy

    Develpoment of combinatorial optimisation for cutting tool path strategy by Alsultaney, Hazem K., Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Ali, Aidy, Mustapha, Faizal

    Published 2009
    “…To simulate the physical removal of material during machining, a finite element model is designed to represent a thin walled workpiece. The target was to develop models which mimic the actual cutting process using the Finite Element Method (FEM) and to validate the developed tool path strategy algorithm with the actual machining process and to programmer the developed algorithm into software. …”
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  7. 7
    ROA-CONS: raccoon optimization job scheduling

    ROA-CONS: raccoon optimization job scheduling by Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan

    Published 2021
    “…In addition, processes and network heterogeneity is another difficulty for the scheduling algorithm. …”
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  8. 8
    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems

    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

    Published 2010
    “…Most of the current methods of crossover determine o®spring by using a stochastic approach and without reference to the objective function with the result being that a potentially optimal solution could be lost through incorrect choices being made in the randomisation process. This thesis focuses on the development of a new stream of crossover within genetic algorithms, called Optimised Crossover Genetic Algorithm (OCGA) for solving combinatorial optimisation problems, which takes into account the objective function in finding the best ofspring solution among an exponentially large number of potential ofspring. …”
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  9. 9
    The concept of wound healing algorithm

    The concept of wound healing algorithm by Jonathan Likoh Juis @ Juise, Teong, Khan Vun, Ryan MacDonnell Andrias, Jetol Bolongkikit, Siti Hasnah Tanalol, Asni Tahir

    Published 2023
    “…The model is developed by taking essential process of wound healing to form the algorithm. …”
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  10. 10
    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network

    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…Moreover, the empirical results obtained showed that incorporating the AHP into Firefly Algorithm improved the accuracy of weight calculations in the multi-objective formulation of the optimisation process. …”
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  11. 11
    An experimental validation and optimisation tool path strategy for thin walled structure

    An experimental validation and optimisation tool path strategy for thin walled structure by Alsultaney, Hazem K., Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Ali, Aidy, Mustapha, Faizal

    Published 2011
    “…To simulate the physical removal of material during machining, a finite element model was designed to represent a thin walled workpiece. The target was to develop models which mimic the actual cutting process using the finite element method (FEM), to validate the developed tool path strategy algorithm with the actual machining process and to programme the developed algorithm into the software. …”
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  12. 12
    Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm

    Optimisation of energy efficient Assembly Sequence Planning using Moth-Flame Optimisation alghorithm by Muhammad Arif, Abdullah

    Published 2019
    “…For optimisation purpose, this research proposed a relatively new algorithm called the Moth-Flame Optimisation (MFO). …”
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  13. 13
    The application of hybrid artificial intelligence techniques in the optimisation of crude palm oil production

    The application of hybrid artificial intelligence techniques in the optimisation of crude palm oil production by ., Lily Amelia, Wahab, Dzuraidah, Hassan, Azmi

    Published 2008
    “…Two heuristic optimisation methods, ie. Genetic Algorithm (GA) and Direct Random Search are applied to solve this problem. …”
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  14. 14
    Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail

    Hybrid evolutionarybarnacles mating optimisation-artificial neural network based technique for solving economic power dispatch planning and operation / Nor Laili Ismail by Ismail, Nor Laili

    Published 2024
    “…In this study, a new optimisation algorithm termed Hybrid Evolutionary-Barnacles Mating Optimisation (HEBMO) was initially formulated to solve optimisation problems. …”
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  15. 15
    Resource management in grid computing using ant colony optimization

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
    “…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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  16. 16
    Modelling and optimisation of cooling-slope parameters of magnesium AZ91D using improvement multi-objective Jaya approach for predicted feedstock performance

    Modelling and optimisation of cooling-slope parameters of magnesium AZ91D using improvement multi-objective Jaya approach for predicted feedstock performance by Mohd Said, Rahaini, Salleh@Sallehuddin, Roselina, Mohamed Radzi, Norhaizan, Wan Ali, Wan Fahmin Faiz, Mohamad Kamal, Mohamad Ridzuan

    Published 2024
    “…Then, mathematical regression models were developed from the data obtained and implemented as an objective function equation in the MOO optimisation process. …”
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  17. 17
    Completion time driven hyper-heuristic approach for optimisation of scientific workflow scheduling in cloud environment / Ehab Nabiel Mohammad

    Completion time driven hyper-heuristic approach for optimisation of scientific workflow scheduling in cloud environment / Ehab Nabiel Mohammad by Ehab Nabiel , Mohammad

    Published 2018
    “…The second stage (i.e. approach development stage) is the development of the proposed CTDHH approach, which includes two main parts, the cost optimisation model of SWFS and the dynamic hyper-heuristic algorithm. …”
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  18. 18
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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  19. 19
    Review of the research landscape of multi-criteria evaluation and bench- marking processes for many-objective optimisation methods: coherent taxonomy, challenges and recommended solution

    Review of the research landscape of multi-criteria evaluation and bench- marking processes for many-objective optimisation methods: coherent taxonomy, challenges and recommended so... by Mohammed, R. T., Yaakob, R., Zaidan, A. A., Sharef, N. M., Abdullah, R. H., Zaidan, B. B., Dawood, K. A.

    Published 2020
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  20. 20
    Optimisation and control of fed-batch yeast production using q-learning

    Optimisation and control of fed-batch yeast production using q-learning by Helen, Chuo Sin Ee

    Published 2013
    “…QLE signifies the importance of exploration from time to time based on the developed “past experience” in Q-table to optimise the process. …”
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