JOURNAL ARTICLE

Multi-Objective Robust Design Optimisation Using Hierarchical Asynchronous Parallel Asynchronous Evolutionary Algorithms

Abstract

In this paper, a new Robust Design method is investigated with a hierarchical asynchronous parallel Multi-objective evolutionary optimisation framework to overcome single and multi-point design optimisation problems in Aerodynamics. The single design techniques produce solutions that perform well for the selected design point but have poor off-design performance. Here, we show how the approach can provide robust solutions using game theory in the sense that the solutions are as less insensitive to little changes of the input parameters. Starting from a statistical definition of stability, the method finds, simultaneously Pareto non-dominated solutions for performance and stability which offer alternative choices to the designer.

Keywords:
Asynchronous communication Computer science Stability (learning theory) Point (geometry) Pareto principle Evolutionary algorithm Mathematical optimization Aerodynamics Pareto optimal Multi-objective optimization Algorithm Artificial intelligence Mathematics Machine learning Engineering

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Topics

Advanced Multi-Objective Optimization Algorithms
Physical Sciences →  Computer Science →  Computational Theory and Mathematics
Evolutionary Algorithms and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
Probabilistic and Robust Engineering Design
Social Sciences →  Decision Sciences →  Statistics, Probability and Uncertainty
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