Biobjective Performance Assessment with the COCO Platform
Dimo Brockhoff, Tea Tu\v{s}ar, Dejan Tu\v{s}ar, Tobias Wagner,, Nikolaus Hansen, Anne Auger
TL;DR
This paper discusses a method for evaluating multi-objective optimizers using the COCO platform, focusing on hypervolume-based performance metrics and runtime until targets are achieved.
Contribution
It introduces a performance assessment framework for biobjective optimization within the COCO platform, emphasizing hypervolume metrics and runtime analysis.
Findings
Hypervolume effectively measures optimizer quality.
Runtime until target hypervolume is achieved is a key performance indicator.
The approach enables comparative analysis of biobjective optimizers.
Abstract
This document details the rationales behind assessing the performance of numerical black-box optimizers on multi-objective problems within the COCO platform and in particular on the biobjective test suite bbob-biobj. The evaluation is based on a hypervolume of all non-dominated solutions in the archive of candidate solutions and measures the runtime until the hypervolume value succeeds prescribed target values.
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Taxonomy
TopicsAdvanced Multi-Objective Optimization Algorithms · Metaheuristic Optimization Algorithms Research · Optimal Experimental Design Methods