Evolutionary optimization tools for multi objective design in aerospace engineering: from theory to MDO applications
Gonzalez, Luis F., Periaux, Jacques, Srinivas, K., & Whitney, Eric J. (2004) Evolutionary optimization tools for multi objective design in aerospace engineering: from theory to MDO applications. In Annicchiarico, William, Periaux, Jacques, Cerrolaza, Miguel, & Winter, Gabriel (Eds.) Evolutionary Algorithms And Intelligent Tools In Engineering Optimization. WIT Press (UK), UK.
The purpose of this chapter is to give an overview of evolutionary algorithms and describe a particular multi-objective EA (MOEA) named Hierarchical Asynchronous Parallel Evolutionary Algorithms (HAPEA) and its application to aeronautical design and optimisation problems. The first chapter provides an overview of evolutionary algorithms introduces the main advantages of this derivative free approach and details the HAPEA method. Then the paper focuses on the application of the method to mathematical test problems for which non-dominated solutions of the Pareto front are known. Finally several practical examples illustrate the potential of the method, related to conceptual and detailed multi objective and multi disciplinary design problems in aeronautics.
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