Multi-condition Multi-objective Airfoil Shape Optimisation Using Deep Reinforcement Learning Compared to Genetic Algorithms

Dasun Shalila Balasooriya; Alan Blair; Craig Wheeler; Stephan K. Chalup

doi:10.1007/978-3-031-77432-4_17

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Multi-condition Multi-objective Airfoil Shape Optimisation Using Deep Reinforcement Learning Compared to Genetic Algorithms

Dasun Shalila Balasooriya Alan Blair Craig Wheeler Stephan K. Chalup

Year: 2024 Communications in computer and information science Pages: 243-258 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-031-77432-4_17

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Keywords:

Reinforcement learning Airfoil Computer science Artificial intelligence Genetic algorithm Algorithm Machine learning Engineering Structural engineering

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Advanced Multi-Objective Optimization Algorithms

Physical Sciences → Computer Science → Computational Theory and Mathematics

Topology Optimization in Engineering

Physical Sciences → Engineering → Civil and Structural Engineering

Probabilistic and Robust Engineering Design

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

Multi-condition Multi-objective Airfoil Shape Optimisation Using Deep Reinforcement Learning Compared to Genetic Algorithms

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