MECHBench: A Set of Black-Box Optimization Benchmarks originated from Structural Mechanics

TL;DR

This paper introduces MECHBench, a new set of black-box optimization benchmarks based on structural mechanics, specifically vehicle crashworthiness, to better evaluate algorithms in realistic engineering scenarios.

Contribution

It presents a curated benchmark suite rooted in structural mechanics, addressing the gap between synthetic benchmarks and real-world engineering problems.

Findings

Benchmarks derived from vehicle crashworthiness scenarios.

Guidelines provided for using the benchmark suite.

Addresses limitations of existing synthetic benchmarks.

Abstract

Benchmarking is essential for developing and evaluating black-box optimization algorithms, providing a structured means to analyze their search behavior. Its effectiveness relies on carefully selected problem sets used for evaluation. To date, most established benchmark suites for black-box optimization consist of abstract or synthetic problems that only partially capture the complexities of real-world engineering applications, thereby severely limiting the insights that can be gained for application-oriented optimization scenarios and reducing their practical impact. To close this gap, we propose a new benchmarking suite that addresses it by presenting a curated set of optimization benchmarks rooted in structural mechanics. The current implemented benchmarks are derived from vehicle crashworthiness scenarios, which inherently require the use of gradient-free algorithms due to the non-smooth, highly non-linear nature of the underlying models. Within this paper, the reader will find descriptions of the physical context of each case, the corresponding optimization problem formulations, and clear guidelines on how to employ the suite.