Privacy sets for constrained space-filling

TL;DR

This paper introduces privacy sets as a new approach for constrained space-filling, providing a typology and a heuristic algorithm to improve coverage in complex sampling problems.

Contribution

It proposes the concept of privacy sets for constrained space-filling and presents a heuristic algorithm to enhance sampling efficiency.

Findings

The privacy set approach improves space-filling performance.

The heuristic algorithm performs well on benchmark examples.

A new typology for constrained space-filling methods is established.

Abstract

The paper provides typology for space filling into what we call "soft" and "hard" methods along with introducing the central notion of privacy sets for dealing with the latter. A heuristic algorithm based on this notion is presented and we compare its performance on some well-known examples.