@inproceedings{37b211fe9a6d46c4a1dd537e27110212,
title = "Algorithm and experiment design with heuristiclab: An open source optimization environment for research and education",
abstract = "The tutorial demonstrates how to apply and analyze metaheuristics using HeuristicLab, an open source optimization environment. It will be shown how to parameterize and execute evolutionary algorithms to solve combinatorial optimization problems (traveling salesman, vehicle routing) as well as data analysis problems (regression, classification). The attendees will learn how to assemble different algorithms and parameter settings to a large scale optimization experiment and how to execute such experiments on multi-core or cluster systems. Furthermore, the experiment results will be compared using HeuristicLab's interactive charts for visual and statistical analysis to gain knowledge from the executed test runs. To complete the tutorial, it will be sketched briefly how HeuristicLab can be extended with further optimization problems and how custom optimization algorithms can be modeled using the graphical algorithm designer. Additional details on HeuristicLab can be found at http://dev.heuristiclab.com.",
keywords = "algorithm analysis, algorithm modeling, algorithm test, heuristic optimization software systems, heuristiclab",
author = "Stefan Wagner and Gabriel Kronberger",
year = "2011",
doi = "10.1145/2001858.2002143",
language = "English",
isbn = "9781450306904",
series = "Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication",
pages = "1411--1438",
booktitle = "Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication",
note = "13th Annual Genetic and Evolutionary Computation Conference, GECCO'11 ; Conference date: 12-07-2011 Through 16-07-2011",
}