Combining drift analysis and generalized schema theory to design efficient hybrid and/or mixed strategy EAs

Boris Mitavskiy, Jun He

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

116 Downloads (Pure)

Abstract

Hybrid and mixed strategy EAs have become rather popular for tackling various complex and NP-hard optimization problems. While empirical evidence suggests that such algorithms are successful in practice, rather little theoretical support for their success is available, not mentioning a solid mathematical foundation that would provide guidance towards an efficient design of this type of EAs. In the current paper we develop a rigorous mathematical framework that suggests such designs based on generalized schema theory, fitness levels and drift analysis. An example-application for tackling one of the classical NP-hard problems, the "single-machine scheduling problem" is presented.
Original languageEnglish
Title of host publication2013 IEEE Congress on Evolutionary Computation
PublisherIEEE Press
Pages2028-2036
ISBN (Electronic)978-1-4799-0452-5
ISBN (Print)978-1-4799-0453-2
DOIs
Publication statusPublished - 01 Jun 2013
Event2013 IEEE Congress on Evolutionary Computation (CEC) - Cancun, Mexico
Duration: 20 Jun 201323 Jun 2013

Conference

Conference2013 IEEE Congress on Evolutionary Computation (CEC)
Country/TerritoryMexico
CityCancun
Period20 Jun 201323 Jun 2013

Fingerprint

Dive into the research topics of 'Combining drift analysis and generalized schema theory to design efficient hybrid and/or mixed strategy EAs'. Together they form a unique fingerprint.

Cite this