Cascading CMA-ES Instances for Generating Input-diverse Solution Batches

Genetic and Evolutionary Computation Conference Companion (GECCO Companion), pp. 1900–1908

Abstract

Rather than obtaining a single good solution for a given optimization problem, users often seek alternative design choices, because the best-found solution may perform poorly with respect to additional objectives or constraints that are difficult to capture into the modeling process. Aiming for batches of diverse solutions of high quality is often desirable, as it provides flexibility to accommodate post-hoc user preferences. At the same time, it is crucial that the quality of the best solution found is not compromised.

Authors 5

1. Maria Laura Santoni

   Centre National de la Recherche Scientifique · Sorbonne Université

   Affiliation as printed

   CNRS, Paris, France

   Sorbonne Université, Paris, France

2. Christoph Dürr

   Centre National de la Recherche Scientifique · Sorbonne Université

   Affiliation as printed

   CNRS, Paris, France

   Sorbonne Université, Paris, France

3. Carola Doerr

   Centre National de la Recherche Scientifique · Sorbonne Université

   Affiliation as printed

   CNRS, Paris, France

   Sorbonne Université, Paris, France

4. Mike Preuß Aachen

   Leiden University

   Affiliation as printed

   Universiteit Leiden, Leiden, Netherlands

5. Elena Raponi Aachen

   Leiden University

   Affiliation as printed

   Universiteit Leiden, Leiden, Netherlands