TRIOPT: a triangulation-based partitioning algorithm for global optimization

A novelty in the search scheme proposed here is that once a partition narrows down to a small size, its vertices are eliminated from the available sample set. This changes global information on the best solution and triggers a re-calculation of transformed values. Hence, revised entropies change the direction of the search to new areas. The latter scheme leads to a dynamic parallel search policy which is based on an entropy cut. The tree adopts flexible breadth depending on the status of the search. In the experimental results it is demonstrated that TRIOPTs performance is compatible and often better than that of a well-known response surface methodology and two other efficient black box partitioning approaches proposed for global optimization.