R2 v2: The Pareto-Compliant R2 Indicator for Better Benchmarking in Bi-Objective Optimization

In multi-objective optimization, set-based quality indicators are a cornerstone of benchmarking and performance assessment. They capture the quality of a set of tradeoff solutions by reducing it to a scalar number. One of the most commonly used setbased metrics is the R2 indicator, which describes the expected utility of a solution set to a decision-maker under a distribution of utility functions. Typically, this indicator is applied by discretizing the latter distribution, yielding a weakly Pareto-compliant indicator. In consequence, adding a nondominated or dominating solution to a solution set may - but does not have to - improve the indicator's value. In this paper, we reinvestigate the R2 indicator under the premise that we have a continuous, uniform distribution of (Tchebycheff) utility functions. We analyze its properties in detail, demonstrating that this continuous variant is indeed Pareto-compliant - that is, any beneficial solution will improve the metric's value. Additionally, we provide efficient computational procedures that (a) compute this metric for bi-objective problems in O(NlogN), and (b) can perform incremental updates to the indicator whenever solutions are added to (or removed from) the current set of solutions, without needing to recompute the indicator for the entire set. As a result, this work contributes to the state-of-the-art Pareto-compliant unary performance metrics, such as the hypervolume indicator, offering an efficient and promising alternative.

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Publication Details

Journal
Evolutionary Computation
Published
2025-10-09
DOI
https://doi.org/10.1162/evco.a.366
Primary Topic
Advanced Multi-Objective Optimization Algorithms
Type
article
Field-Weighted Citation Impact
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article

R2 v2: The Pareto-Compliant R2 Indicator for Better Benchmarking in Bi-Objective Optimization

Pascal Kerschke, Lennart Schäpermeier
Evolutionary Computation
Advanced Multi-Objective Optimization Algorithms
article

R2 v2: The Pareto-Compliant R2 Indicator for Better Benchmarking in Bi-Objective Optimization

Pascal Kerschke, Lennart Schäpermeier
article en

Abstract

In multi-objective optimization, set-based quality indicators are a cornerstone of benchmarking and performance assessment. They capture the quality of a set of tradeoff solutions by reducing it to a scalar number. One of the most commonly used setbased metrics is the R2 indicator, which describes the expected utility of a solution set to a decision-maker under a distribution of utility functions. Typically, this indicator is applied by discretizing the latter distribution, yielding a weakly Pareto-compliant indicator. In consequence, adding a nondominated or dominating solution to a solution set may - but does not have to - improve the indicator's value. In this paper, we reinvestigate the R2 indicator under the premise that we have a continuous, uniform distribution of (Tchebycheff) utility functions. We analyze its properties in detail, demonstrating that this continuous variant is indeed Pareto-compliant - that is, any beneficial solution will improve the metric's value. Additionally, we provide efficient computational procedures that (a) compute this metric for bi-objective problems in O(NlogN), and (b) can perform incremental updates to the indicator whenever solutions are added to (or removed from) the current set of solutions, without needing to recompute the indicator for the entire set. As a result, this work contributes to the state-of-the-art Pareto-compliant unary performance metrics, such as the hypervolume indicator, offering an efficient and promising alternative.

Evolutionary Computation
Technische Universität Dresden (DE)
Openalex Percentile: Top 70%
Advanced Multi-Objective Optimization Algorithms
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