Opportunistic Fitness Evaluation in a Genetic Algorithm for Civil Engineering Design Optimization

The process of large structure design in civil engineering relies primarily on trial and error, guided by experience. We apply genetic algorithms to search for valid designs (satisfying all design constraints), minimizing total weight. The fitness evaluation has two components. Evaluating the validity of a candidate solution is very expensive, but the total weight can be evaluated independently and relatively cheaply. We demonstrate two techniques for using the inexpensive quality evaluation to decide whether or not the expensive validity evaluation is worth the investment of time it requires. We also use operators that reflect domain expert knowledge about design improvement techniques in order to improve convergence.