Evolutionary algorithms for constrained engineering problems
Computers and Industrial Engineering
Simulation optimization: methods and applications
Proceedings of the 29th conference on Winter simulation
Direct search methods: then and now
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. IV: optimization and nonlinear equations
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Some Guidelines for Genetic Algorithms with Penalty Functions
Proceedings of the 3rd International Conference on Genetic Algorithms
Improved genetic algorithm for multidisciplinary optimization of composite laminates
Computers and Structures
Hi-index | 0.00 |
The main goal of the present study is to optimise the precharge conditions such as the precharge location and dimensions that give significant effects on the mechanical performance of composite structures manufactured by the compression moulding process. As preliminary step of optimisation, we developed a manufacturing simulation program to predict the fibre volume fraction and fibre orientation. And coupled with this simulation program and a structural analysis program, a genetic algorithm (GA) is implemented to optimise the precharge conditions. The penalty function method and the repair algorithm are modified for handling constraints. The repair algorithm is applied to a symmetric structure and an arbitrary shape structure to find optimal precharge conditions.