*Result*: Improving experimental design for automatic algorithm selection techniques by using a virtual best solver
Title:
Improving experimental design for automatic algorithm selection techniques by using a virtual best solver
Authors:
Source:
ORBEL, Antwerpen, 5-6 February 2015
Publication Year:
2015
Subject Terms:
Document Type:
lecture
File Description:
application/pdf
Language:
English
Availability:
Rights:
info:eu-repo/semantics/openAccess ; public
Accession Number:
edsbas.99CC6190
Database:
BASE
*Further Information*
*Evidence of the quality of metaheuristics is usually empirical. Common experimental design consists of testing a technique on benchmark instances. The goal of this article is first, to expose the flaws of this approach. Then, to illustrate how the experimental design can be improved by calculating a performance upper bound based on the instances and algorithms used. And ultimately, to introduce a tighter upper bound that also takes information about the problem features into account. ; sponsorship: KU Leuven, Department of Computer Science, CODeS \& iMinds-ITEC ; status: Published*