Application of genetic programming and response surface methodology to optimization and inverse problems

Reliability-based design optimisation of structural systems using high-order analytical moments

“…Genetic programming is an approach inspired by biological evolution, whereby, using an evolutionary algorithm, a set of model parameters will evolve to optimise the objective function. The use of genetic programming to build metamodels was first reported in the late 1990s [61], whereas the earlier works of using polynomials as the node functions in genetic programming were reported in the early 2000s [62]. A recent study [52] introduced a more accurate and efficient polynomial genetic programming algorithm for response surface modelling, and went on to demonstrate that it can reliably model highly nonlinear functions.…”