Topographical Mapping assisted Evolutionary Search for Multilevel Optimization

In many problems in science and engineering, it is often the case that there exist a number of computational models to simulate the problem at hand. These models are usually trade-offs between accuracy and computational expense. Given a limited computation budget, there is need to develop a framework for selecting between different models in a sensible fashion during the search. The method proposed here is based on the construction of a heteroassociative mapping to estimate the differences between models, and using this information to guide the search. The proposed framework is tested on the problem of minimizing the transmitted vibration energy in a satellite boom.