Hot off the Press: BONO-Bench: A Comprehensive Test Suite for Bi-objective Numerical Optimization with Traceable Pareto Sets
TL;DR
BONO-Bench is presented, a recently proposed problem generator and benchmark set for bi-objective numerical optimization that enables best practices for empirical runtime analysis of optimizers using reference solutions that can be approximated to an arbitrary degree, resulting in precise target values for the hypervolume and exact R2 indicators.
Abstract
The evaluation of heuristic optimizers on test problems, better known as benchmarking, is a cornerstone of research in multiobjective optimization. However, many frequently used test problems either feature a limited degree of optimization challenges or have poorly understood reference solutions. Here, we present an overview of BONO-Bench [5], a recently proposed problem generator and benchmark set for bi-objective numerical optimization. Building on convex-quadratic problems, it features diverse challenges ranging from different levels of conditioning, shapes of Pareto set and front as well as plateaus to different structured and unstructured multimodality patterns. Furthermore, we enable best practices for empirical runtime analysis of optimizers using reference solutions that can be approximated to an arbitrary degree, resulting in precise target values for the hypervolume and exact R2 indicators.