OCAIJul 1, 2024

R2 v2: The Pareto-compliant R2 Indicator for Better Benchmarking in Bi-objective Optimization

arXiv:2407.01504v22 citationsh-index: 23
Originality Incremental advance
AI Analysis

This work offers an incremental improvement for researchers and practitioners in optimization benchmarking by enhancing the reliability and efficiency of performance metrics.

The paper tackles the issue of weakly Pareto-compliant R2 indicators in multi-objective optimization by proposing a continuous variant that ensures Pareto compliance, where any beneficial solution improves the metric's value, and provides efficient computational procedures with O(N log N) complexity for bi-objective problems.

In multi-objective optimization, set-based quality indicators are a cornerstone of benchmarking and performance assessment. They capture the quality of a set of trade-off solutions by reducing it to a scalar number. One of the most commonly used set-based 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 $\mathcal O (N \log N)$, 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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