When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems

Genetic and Evolutionary Computation Conference (GECCO), pp. 856–863

Abstract

The domain of an optimization problem is seen as one of its most important characteristics. In particular, the distinction between continuous and discrete optimization is rather impactful. Based on this, the optimizing algorithm, analyzing method, and more are specified. However, in practice, no problem is ever truly continuous. Whether this is caused by computing limits or more tangible properties of the problem, most variables have a finite resolution.

Authors 6

1. André Thomaser Aachen

   Leiden University · BMW (Germany)

   Affiliation as printed

   BMW AG, Munich, Germany

   Leiden University, Munich, Germany

   BMW AG, Munich, Germany Leiden University, Munich, Germany

2. Jacob de Nobel Aachen

   Leiden University

   Affiliation as printed

   Leiden University, Leiden, Netherlands

3. Diederick Vermetten Aachen

   Leiden University

   Affiliation as printed

   Leiden University, Leiden, Netherlands

4. Furong Ye Aachen

   Leiden University

   Affiliation as printed

   Leiden University, Leiden, Netherlands

5. Thomas Bäck Aachen

   Leiden University

   Affiliation as printed

   Leiden University, Leiden, Netherlands

6. Anna V. Kononova Aachen

   Leiden University

   Affiliation as printed

   Leiden University, Leiden, Netherlands