Search Results - (( java evolution optimization algorithm ) OR ( based conflict evolution algorithm ))

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  1. 1
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…The aim of this evolution is to reflect the unseen time overhead incurred by optimal real-time algorithm, represented by LRE-TL, which might hinder the claimed optimality of such algorithms when they are practically implemented. …”
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  2. 2
    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses

    Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses by Tarajo, Buba Ahmed, Lee, Lai Soon

    Published 2019
    “…From the perspective of multiobjective optimization, the proposed hybrid algorithm is able to produce a diverse set of nondominated solutions, given the passengers’ and operators’ costs are conflicting objectives.…”
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  3. 3
    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE)

    Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE) by Tijani, Ismaila Bayo, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2015
    “…Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance. …”
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  4. 4
    Control of an inverted pendulum using MODE-based optimized LQR controller

    Control of an inverted pendulum using MODE-based optimized LQR controller by Tijani, Ismaila B., Akmeliawati, Rini, Abdullateef, Ayodele I.

    Published 2013
    “…Hence, a Multiobjective differential evolution algorithm is proposed to design an LQR controller with optimal compromise between the conflicting control objectives. …”
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  5. 5
    A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence

    A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence by Tse, Guan Tan, Teo, Jason Tze Wi, Rayner Alfred, Kim, On Chin

    Published 2013
    “…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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  6. 6
    Automatic generation of Swarm Robotic behaviors using multi-objective evolution

    Automatic generation of Swarm Robotic behaviors using multi-objective evolution by Chin, Kim On, Teo, Jason, Azali, Saudi

    Published 2009
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  7. 7
    A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence

    A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence by Tse, Guan Tan, Jason, Teo, Kim, On Chin, Alfred, Rayner

    Published 2013
    “…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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  8. 8
    Pareto ensembles for evolutionary synthesis of Neurocontrollers in a 2D maze-based video game

    Pareto ensembles for evolutionary synthesis of Neurocontrollers in a 2D maze-based video game by Tse, Guan Tan, Jason Teo, Chin, Kim On, Patricia Anthony

    Published 2013
    “…In this paper, we present a study of evolving artificial neural network controllers for autonomously playing maze-based video game. A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. …”
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  9. 9
    Pareto Ensembles for evolutionary Synthesis of Neurocontrollers in a 2D Maze-based video game

    Pareto Ensembles for evolutionary Synthesis of Neurocontrollers in a 2D Maze-based video game by Tse, Guan Tan, Jason Teo, Kim, On Chin, Patricia Anthony

    Published 2013
    “…In this paper, we present a study of evolving artificial neural network controllers for autonomously playing maze-based video game. A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. …”
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  10. 10
    Evolving neural controllers for terrestrial and extraterrestrial locomotion in an artificial quadruped

    Evolving neural controllers for terrestrial and extraterrestrial locomotion in an artificial quadruped by Teo, Jason Tze Wi

    Published 2005
    “…The Paretofrontier Differential Evolution (PDE) algorithm is used to generate a Pareto optimal set of artificial neural networks that optimize the conflicting objectives of maximizing locomotion behavior and minimizing neural network complexity. …”
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  11. 11
    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems

    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems by Salman, Mustafa Ismael

    Published 2015
    “…In the frequency domain of this scheduler, a new mapping between channel quality indicator (CQI) and modulation and coding scheme (MCS) is proposed to find the tradeoff between conflicting criteria. On the user side, a partial channel feedback scheme based on an adaptive CQI threshold is developed. …”
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  12. 12
    Mobility management for seamless handover in carrier aggregation heterogeneous networks deployment scenario of long term evolution-advanced

    Mobility management for seamless handover in carrier aggregation heterogeneous networks deployment scenario of long term evolution-advanced by Ahmed-Abdulazeez, Mariam Ovayioza

    Published 2018
    “…Secondly, a Hybrid Handover Parameters Optimization algorithm based on Enhanced Weight Performance (HHPO) is introduced to optimize, select suitable Handover Control Parameters (HCP) and to manage the conflict that may occur among self-optimization functions. …”
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  13. 13
    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Kim On Chin, Jason Teo

    Published 2009
    “…The Pareto-frontier Differential Evolution (PDE) algorithm is utilized to generate the Pareto optimal sets through a 3-layer feed-forward artificial neural network that optimize the conflicting objectives of robot behavior and network complexity, where the two different types of robot behaviors are phototaxis and RF-localization, respectively. …”
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  14. 14
    Handover algorithm with joint processing technique based on coordinated multipoint (COMP) transmission and reception in LTE-advanced heterogeneous network / Muhammad Aiman Zainali

    Handover algorithm with joint processing technique based on coordinated multipoint (COMP) transmission and reception in LTE-advanced heterogeneous network / Muhammad Aiman Zainali by Zainali, Muhammad Aiman

    Published 2020
    “…In this research, a JP based on CoMP handover algorithm in LTE-A network is proposed. …”
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  15. 15
    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition

    Artificial Neural Controller Synthesis in Autonomous Mobile Cognition by Chin Kim On, Jason Teo

    Published 2009
    “…The Pareto-frontier Differential Evolution (PDE) algorithm is utilized to generate the Pareto optimal sets through a 3-layer feed-forward artificial neural network that optimize the conflicting objectives of robot behavior and network complexity, where the two different types of robot behaviors are phototaxis and RF-localization, respectively. …”
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  16. 16
    Fully decentralized, cost-effective energy demand response management system with a smart contracts-based optimal power flow solution for smart grids

    Fully decentralized, cost-effective energy demand response management system with a smart contracts-based optimal power flow solution for smart grids by Merrad, Yacine, Habaebi, Mohamed Hadi, Toha, Siti Fauziah, Islam, Md Rafiqul, Gunawan, Teddy Surya, Mesri, Mokhtaria

    Published 2022
    “…Due to the complexity of formulating and solving OPF problems in the presence of renewable energy sources, researchers have focused on mathematical modeling and effective solution algorithms for such optimization problems. However, the control of power generation according to a defined OPF solution is still based on centralized control and management units owned by the DSO. …”
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