Abstract
The inception of algorithm portfolios has had a dramatic impact on constraint programming, operations research, and many other fields. Based on the observation that solvers have complementary strengths and therefore exhibit incomparable behavior on different problem instances, the ideas of running multiple solvers in parallel or selecting one solver based on the features of a given instance were introduced. Appropriately, these approaches have been named algorithm portfolios. Portfolio research has led to a wealth of different approaches and an amazing boost in solver performance in the past decade. This chapter demonstrates how the ISAC methodology can be applied to this task. Ultimately, here we aim to develop algorithm portfolios that are able to deal effectively with a vast range of input instances from a variety of sources.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
