Finding robust solutions to dynamic optimization problems

Haobo FU, Bernhard SENDHOFF, Ke TANG, Xin YAO

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

38 Citations (Scopus)

Abstract

Most research in evolutionary dynamic optimization is based on the assumption that the primary goal in solving Dynamic Optimization Problems (DOPs) is Tracking Moving Optimum (TMO). Yet, TMO is impractical in cases where keeping changing solutions in use is impossible. To solve DOPs more practically, a new formulation of DOPs was proposed recently, which is referred to as Robust Optimization Over Time (ROOT). In ROOT, the aim is to find solutions whose fitnesses are robust to future environmental changes. In this paper, we point out the inappropriateness of existing robustness definitions used in ROOT, and therefore propose two improved versions, namely survival time and average fitness. Two corresponding metrics are also developed, based on which survival time and average fitness are optimized respectively using population-based algorithms. Experimental results on benchmark problems demonstrate the advantages of our metrics over existing ones on robustness definitions survival time and average fitness. © Springer-Verlag Berlin Heidelberg 2013.
Original languageEnglish
Title of host publicationApplications of Evolutionary Computing : 16th European Conference, EvoApplications 2013, Vienna, Austria, April 3-5, 2013, Proceedings
EditorsAnna I. ESPARCIA-ALCÁZAR
PublisherSpringer
Pages616-625
Number of pages10
ISBN (Electronic)9783642371929
ISBN (Print)9783642371912
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event16th European Conference on the Applications of Evolutionary Computation - Vienna, Austria
Duration: 3 Apr 20135 Apr 2013

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume7835
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameTheoretical Computer Science and General Issues
PublisherSpringer
ISSN (Print)2512-2010
ISSN (Electronic)2512-2029

Conference

Conference16th European Conference on the Applications of Evolutionary Computation
Abbreviated titleEvoApplications 2013
Country/TerritoryAustria
CityVienna
Period3/04/135/04/13

Keywords

  • Evolutionary Dynamic Optimization
  • Population-Based Search Algorithms
  • Robust Optimization Over Time

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