Generating Easy and Hard Problems using the Proximate Optimality Principle

Benchmarks are important for comparing performance of optimisation algorithms, but we can select instances that present our algorithm favourably, and dismiss those on which our algorithm under-performs. Also related are automated design of algorithms, which use problem instances (benchmarks) to train an algorithm: careful choice of instances is needed for the algorithm to generalise. We sweep parameter se ings of di erential evolution to applied to the BBOB benchmarks. Several benchmark functions are highly correlated. is may lead to the false conclusion that an algorithm performs well in general, when it performs poorly on a few key instances. ese correlations vary with the number of evaluations.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Generating Easy and Hard Problems using the Proximate Optimality Principle

Cited by 2 publications

References 10 publications

Interpolated continuous optimisation problems with tunable landscape features

Interpolated continuous optimisation problems with tunable landscape features

Investigating benchmark correlations when comparing algorithms with parameter tuning

Contact Info

Product

Resources

About