A MIXED EVOLUTIONARY HEURISTIC APPROACH TO SHAPE OPTIMIZATION/

The problem of finding the optimal shape of a continuous structure is addressed using, alternatively, heuristic, evolutionary and mixed evol utionary and heuristic optimization strategies. Boundaries are represe nted by B-splines. Two heuristics for minimizing the weight of a struc ture subject to limits on von Mises stresses and geometrical constrain ts are implemented: 'generalized biological growth' and 'penalized bio logical growth'. Penalized biological growth adds to generalized biolo gical growth a control for shape changes. This control is based on the overall state of constraints satisfaction in the structure. The two h euristics are very efficient at improving the designs, but they do not yield globally optimal shapes. Therefore, they are interfaced with an evolutionary optimizer. Different strategies for mixing evolutionary search and biological growth are compared. Results are obtained for fa n disk shape problems. They show that mixing evolutionary search with biological growth improves the efficiency of the optimization. The met hod offers to the designer new paths for a better component determinat ion. (C) 1998 John Wiley & Sons, Ltd.