Necessary and Sufficient Conditions for Surrogate Functions of Pareto Frontiers and Their Synthesis Using Gaussian Processes

TL;DR

This paper establishes the fundamental conditions for surrogate functions to accurately represent Pareto frontiers in multi-objective optimization, enabling more reliable and flexible modeling using Gaussian processes with monotonicity constraints.

Contribution

It introduces necessary and sufficient conditions for surrogate functions of Pareto frontiers and demonstrates their implementation with Gaussian processes incorporating monotonicity constraints.

Findings

Constrained Gaussian processes effectively approximate Pareto frontiers.

Existing methods often violate the conditions for valid frontiers.

Proposed approach improves surrogate quality in challenging optimization instances.

Abstract

This paper introduces the necessary and sufficient conditions that surrogate functions must satisfy to properly define frontiers of non-dominated solutions in multi-objective optimization problems. These new conditions work directly on the objective space, thus being agnostic about how the solutions are evaluated. Therefore, real objectives or user-designed objectives' surrogates are allowed, opening the possibility of linking independent objective surrogates. To illustrate the practical consequences of adopting the proposed conditions, we use Gaussian processes as surrogates endowed with monotonicity soft constraints and with an adjustable degree of flexibility, and compare them to regular Gaussian processes and to a frontier surrogate method in the literature that is the closest to the method proposed in this paper. Results show that the necessary and sufficient conditions proposed here are finely managed by the constrained Gaussian process, guiding to high-quality surrogates capable of suitably synthesizing an approximation to the Pareto frontier in challenging instances of multi-objective optimization, while an existing approach that does not take the theory proposed in consideration defines surrogates which greatly violate the conditions to describe a valid frontier.