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  1. 1
    Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm

    Modelling and optimisation of oil palm trunk core biodelignification using neural network and genetic algorithm by Abdul Sahli, Fakharudin, Norazwina, Zainol, Zulsyazwan, Ahmad Khushairi

    Published 2019
    “…These models were used to find the optimised the network output using genetic algorithm search. …”
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  2. 2
    Optimisation of multi-stage production-inspection stations using genetic algorithm

    Optimisation of multi-stage production-inspection stations using genetic algorithm by Hassan, Azmi, Pham, Duc Trung

    Published 2000
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  3. 3
    Optimised crossover genetic algorithm for capacitated vehicle routing problem

    Optimised crossover genetic algorithm for capacitated vehicle routing problem by Nazif, Habibeh, Lee, Lai Soon

    Published 2012
    “…The proposed algorithm uses an optimised crossover operator designed by a complete undirected bipartite graph to find an optimal set of delivery routes satisfying the requirements and giving minimal total cost. …”
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  4. 4
    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems

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

    Published 2010
    “…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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  5. 5
    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 this research, a Genetic-based Algorithm was used as an optimisation approach. …”
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  6. 6
    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production

    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production by Abdul Sahli, Fakharudin, Md Nasir, Sulaiman, Jailani, Salihon, Norazwina, Zainol

    Published 2013
    “…This paper proposed a framework to model and optimises a biogas production using artificial neural networks and genetic algorithms. …”
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  7. 7
    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production

    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of biogas production by Fakharudin, Abdul Sahli, Sulaiman, Md Nasir, Salihon, Jailani, Zainol, Norazwina

    Published 2013
    “…This paper proposed a framework to model and optimises a biogas production using artificial neural networks and genetic algorithms. …”
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  8. 8
    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of blogas production

    Implementing artificial neural networks and genetic algorithms to solve modeling and optimisation of blogas production by Fakharudin, Abdul Sahli, Sulaiman, Md Nasir, Salihon, Jailani, Zainol, Norazwina

    Published 2013
    “…This paper proposed a framework to model and optimises a biogas production using artificial neural networks and genetic algorithms.The intelligence computation was applied to achieve a better model and optimisation compared to a mathematical modeling.Two training approaches were used to train a set of neural networks design. …”
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  9. 9
    Genetic algorithm optimisation for fuzzy control of wheelchair lifting and balancing

    Genetic algorithm optimisation for fuzzy control of wheelchair lifting and balancing by Ahmad, Salmiah, Tokhi, M. Osman, Toha, Siti Fauziah

    Published 2009
    “…General rules of thumb allow heuristic tuning of the parameters but a proper optimisation mechanism will perform better. Genetic Algorithm is used to control the two-wheeled wheelchair and results show that the optimised parameters give better system performance.…”
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  10. 10
    Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation

    Multi-objective model optimisation using genetic algorithms for pleurotus sp. cultivation by Norazwina, Zainol, Abdul Sahli, Fakharudin, Noor Athirah, Dzulkefli, M. F., A. Bakar

    Published 2020
    “…For this type of problem, multi-objective genetic algorithm was chosen as the methodology, specifically using NSGA-II algorithm. …”
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  11. 11
    Dual-head marking performance optimisation via evolutionary solutions

    Dual-head marking performance optimisation via evolutionary solutions by Koh J., Tiong S.K., Aris I.B., Mahmoud S.

    Published 2023
    “…This paper presents a new approach to optimise the performance of a multi-head marking system in terms of its marking speed This processing method named as MMA (Molecular Marking Optimisation algorithm) will adopt the use of Genetic Algorithm. …”
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  12. 12
    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
    “…The performance of the proposed algorithm was compared with a pre-determined exponential feeding profile and a genetic algorithm. …”
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  13. 13
    Analysis of Strength on Thick Plate Part using Genetic Algorithm Optimisation Method

    Analysis of Strength on Thick Plate Part using Genetic Algorithm Optimisation Method by S. M., Azlan, Z., Shayfull, S. M., Nasir, Mohd Sazli, Saad, Mohd Rashidi, Maarof, M., Fathullah

    Published 2016
    “…This study focuses on the optimisation of the injection moulding parameters to maximise the strength ofmoulded parts using a simulation software. …”
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  14. 14
    Hybrid genetic algorithm for uncapacitated university examination timetabling problem

    Hybrid genetic algorithm for uncapacitated university examination timetabling problem by Ishak, Suhada

    Published 2015
    “…The main components of the genetic operators in a Genetic Algorithm (GA) will be tested and the best combination of the genetic operators will be adopted to construct a Pure Genetic Algorithm (PGA). …”
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  15. 15
    Genetic algorithm for control and optimisation of exothermic batch process

    Genetic algorithm for control and optimisation of exothermic batch process by Tan, Min Keng

    Published 2013
    “…As such, another approach, GA is proposed to optimise the productivity without referring to a predetermined profile, namely genetic algorithm optimiser (GAO). …”
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  16. 16
    Active vibration control using pole placement method of a flexible plate structure optimised by genetic algorithm

    Active vibration control using pole placement method of a flexible plate structure optimised by genetic algorithm by Tuan Abdul Rahman, Tuan Ahmad Zahidi, Mat Darus, Intan Zaurah

    Published 2012
    “…A second order ARX model optimised by genetic algorithm (GA) is employed to represent the dynamical system and then feedback controller using pole placement method is exploited to stabilise the system and attenuate the disturbance vibration. …”
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  17. 17
    Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II

    Optimisation of Assembly Line Balancing Type-E with Resource Constraints using NSGA-II by Masitah, Jusop, M. F. F., Ab Rashid

    Published 2016
    “…Six benchmark problems have been used to test the optimisation algorithm and the results are compared to multi-objective genetic algorithm (MOGA) and hybrid genetic algorithm (HGA). …”
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  18. 18
    Optimised intelligent tilt controller scheme using genetic algorithms

    Optimised intelligent tilt controller scheme using genetic algorithms by Zamzuri, Hairi, Zolotas, Argyrios, Goodall, Roger

    Published 2006
    “…This paper presents work on a fuzzy control design for improving the performance of tilting trains with local-per vehicle control, i.e. without employing precedence control.An optimisation procedure using Genetic Algorithms as employed to determine both the best fuzzy output membership function and best PID controller parameters. …”
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  19. 19
    Solving fuzzy-facilities layout problem using genetic algorithm

    Solving fuzzy-facilities layout problem using genetic algorithm by Purnomo, Muhammad Ridwan Andi, Mandiri, Amalia Ramadhana, Hassan, Azmi

    Published 2013
    “…Further, the obtained matrix is used for layout optimisation that conducted using Genetic Algorithm (GA). …”
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  20. 20
    Manufacturing process planning optimisation in reconfigurable multiple parts flow lines

    Manufacturing process planning optimisation in reconfigurable multiple parts flow lines by Ismail, Napsiah, Musharavati, Farayi, Hamouda, Abdel Magid Salem, Ramli, Abdul Rahman

    Published 2008
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