Skip to main content

A Concept for Real-Valued Multi-objective Landscape Analysis Characterizing Two Biochemical Optimization Problems

  • Conference paper
  • First Online:
Book cover Applications of Evolutionary Computation (EvoApplications 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9028))

Included in the following conference series:

Abstract

Landscape analysis is an established method to provide an insight into the characteristic properties of an optimization problem with the aim of designing a suitable evolutionary algorithm for a given problem. However, these conventional landscape structures require sophisticated notions for multi-objective optimization problems. This work presents a real-valued multi-objective landscape analysis concept that allows the investigation of multi-objective molecular optimization problems. Sophisticated definitions for ruggedness, correlation and plateaus on multi-objective real-valued landscapes are introduced and indicators are proposed for this purpose. This landscape concept is realized on a generic three- and four-dimensional biochemical minimization problem and the results of this analysis are discussed regarding the design principles of a multi-objective evolutionary algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Merz, P., Freisleben, B.: Fitness landscape analysis and memetic algorithms for the quadratic assignment problem. IEEE Trans. Evol. Comput. 4(4), 337–352 (2000)

    Article  Google Scholar 

  2. Emmerich, M., Lee, B.V.Y., Render, A., Faddiev, E., Kruisselbrink, J., Deutz, A.H.: Analyzing molecular landscapes using random walks and information theory. Chem. Cent. J. 3(1), 20 (2009)

    Article  Google Scholar 

  3. Merkuryeva, G., Bolshakovs, V.: Benchmark fitness landscape analysis. Int. J. Simul. Syst. Sci. Technol. 12(2), 38–45 (2011)

    Google Scholar 

  4. Garrett, D., Dasgupta, D.: Multi-objective landscape analysis and the generalized assignment problem. In: Maniezzo, V., Battiti, R., Watson, J.-P. (eds.) Learning and Intelligent Optimization. LNCS, vol. 5313, pp. 110–124. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  5. Knowles, J.D., Corne, D.W.: Towards landscape analysis to inform the design of a hybrid local search for the multi-objective quadratic assignment problem. In: HIS, pp. 271–279 (2002)

    Google Scholar 

  6. Stadler, P.M.: Fitness Landscape. Lecture Notes in Physics, vol. 585. Springer, Heidelberg (2002)

    Google Scholar 

  7. Reidys, C.M., Stadler, P.F.: Combinatorial landscape. SIAM Rev. 44, 3–54 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  8. Lee, B.V.Y.: Analyzing Molecular Landscapes using Random Walk and Information Theory. LIACS, University of Leiden, Masterthesis (2009)

    Google Scholar 

  9. Tan, P.N., Steinbach, M., Kumar, V.: Introduction to Data Mining. Pearson Addison Wesley, Boston (2006)

    Google Scholar 

  10. Ceperly, D., Chen, Y., Crain, R.V., Meng, X., Mira, A., Rosenthal, J.: Challenges and advances in high dimensional and high complexity monte carlo computation and theory. In: Proceedings of the Workshop at the Banff International Research Station for Mathematical Innovation Discovery (2012)

    Google Scholar 

  11. BioJava, version 3.0.8. http://biojava.org/wiki/Main_Page

  12. Henikoff, S., Henikoff, J.G.: Amino acid substitution matrices from protein blocks. Proc. Natl. Acad. Sci. USA 89(22), 10915–10919 (1992)

    Article  Google Scholar 

  13. Hopp, T.P., Woods, K.R.: A computer programm for predicting protein antigenic determinants. Mol. Immunol. 20(4), 483–489 (1983)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Markus Borschbach .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Rosenthal, S., Borschbach, M. (2015). A Concept for Real-Valued Multi-objective Landscape Analysis Characterizing Two Biochemical Optimization Problems. In: Mora, A., Squillero, G. (eds) Applications of Evolutionary Computation. EvoApplications 2015. Lecture Notes in Computer Science(), vol 9028. Springer, Cham. https://doi.org/10.1007/978-3-319-16549-3_72

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-16549-3_72

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16548-6

  • Online ISBN: 978-3-319-16549-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics