Constraint Method-Based Evolutionary Algorithm (CMEA) for Multiobjective Optimization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Evolutionary and adaptive synthesis methods
Formal engineering design synthesis
International Journal of Computer Applications in Technology
Real-World Applications of Multiobjective Optimization
Multiobjective Optimization
Macro-informatics of cognition and its application for design
Advanced Engineering Informatics
Finite Elements in Analysis and Design
Journal of Computational and Applied Mathematics
ASM '07 The 16th IASTED International Conference on Applied Simulation and Modelling
PSFGA: a parallel genetic algorithm for multiobjective optimization
EUROMICRO-PDP'02 Proceedings of the 10th Euromicro conference on Parallel, distributed and network-based processing
New fitness sharing approach for multi-objective genetic algorithms
Journal of Global Optimization
Structured population genetic algorithms: a literature survey
Artificial Intelligence Review
Hi-index | 0.00 |
This paper discusses the design optimization of a wing for supersonic transport (SST) using a multiple-objective genetic algorithm (MOGA). Three objective functions are used to minimize the drag for supersonic cruise, the drag for transonic cruise, and the bending moment at the wing root for supersonic cruise. The wing shape is defined by 66 design variables. A Euler flow code is used to evaluate supersonic performance, and a potential flow code is used to evaluate transonic performance. To reduce the total computational time, flow calculations are parallelized on an NEC SX-4 computer using 32 processing elements. The detailed analysis of the resulting Pareto front suggests a renewed interest in the arrow wing planform for the supersonic wing