An Enhanced Probability of Improvement Utility Function for Locating Pareto Optimal Solutions
Glenn I. Hawe, Jan K. Sykulski · ePrints Soton (University of Southampton) · 2007
This paper describes a novel utility function for choosing design vectors to evaluate in multi-objective optimization problems which are statistically most probable to be Pareto-optimal, given the points already evaluated. The method is tunable to the number of existing Pareto-optimal solutions that an unevaluated design vector is sought to dominate, is naturally parallelized, and removes any need for combining the multiple objectives into a single objective with a scalarizing function.