Na\"ive restarts of global optimization solvers when operating on multimodal search landscapes may resemble the Coupon's Collector Problem, with a potential to waste significant function evaluations budget on revisiting the same basins of attractions. In this paper, we assess the degree to which such ``duplicate restarts'' occur on standard multimodal benchmark functions, which defines the \textit{redundancy potential} of each particular landscape. We then propose a repelling mechanism to avoid such wasted restarts with the CMA-ES and investigate its efficacy on test cases with high redundancy potential compared to the standard restart mechanism.
Cite
@article{arxiv.2405.01226,
title = {Avoiding Redundant Restarts in Multimodal Global Optimization},
author = {Jacob de Nobel and Diederick Vermetten and Anna V. Kononova and Ofer M. Shir and Thomas Bäck},
journal= {arXiv preprint arXiv:2405.01226},
year = {2024}
}