@inproceedings{888959a4ee6f48ae8528c3724ee04ec5,
title = "Mixed-integer benchmark problems for single- And bi-objective optimization",
abstract = "We introduce two suites of mixed-integer benchmark problems to be used for analyzing and comparing black-box optimization algorithms. They contain problems of diverse difficulties that are scalable in the number of decision variables. The bbob-mixint suite is designed by partially discretizing the established BBOB (Black-Box Optimization Benchmarking) problems. The bi-objective problems from the bbob-biobj-mixint suite are, on the other hand, constructed by using the bbob-mixint functions as their separate objectives. We explain the rationale behind our design decisions and show how to use the suites within the COCO (Comparing Continuous Optimizers) platform. Analyzing two chosen functions in more detail, we also provide some unexpected findings about their properties.",
keywords = "Benchmarking, Mixed-integer optimization, Test function suite, The COCO platform",
author = "Tea Tu{\v s}ar and Dimo Brockhoff and Nikolaus Hansen",
note = "Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s). Publication rights licensed to the Association for Computing Machinery.; 2019 Genetic and Evolutionary Computation Conference, GECCO 2019 ; Conference date: 13-07-2019 Through 17-07-2019",
year = "2019",
month = jul,
day = "13",
doi = "10.1145/3321707.3321868",
language = "English",
series = "GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery, Inc",
pages = "718--726",
booktitle = "GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference",
}