A Tunable Model for Multi-Objective, Epistatic, Rugged, and Neutral Fitness Landscapes

Authors

Abstract

The fitness landscape of a problem is the relation between the solution candidates and their reproduction probability. In order to understand optimization problems, it is essential to also understand the features of fitness landscapes and their interaction. In this paper we introduce a model problem that allows us to investigate many characteristics of fitness landscapes. Specifically noise, affinity for overfitting, neutrality, epistasis, multi-objectivity, and ruggedness can be independently added, removed, and fine-tuned. With this model, we contribute a useful tool for assessing optimization algorithms and parameter settings.

Keywords

Tunable Benchmark Model for ENROOMO, Discrete Search Spaces, Genetic Algorithms, GAs, Epistasis, Neutrality, Ruggedness, Causality, Multi-Objective Optimization, MOOP

BibTeX

@inproceedings{WNSRG2008ATMFMOERANFL,
  author                    = {Thomas Weise and Stefan Niemczyk and Hendrik Skubch and Roland Reichle and Kurt Geihs},
  title                     = {{A Tunable Model for Multi-Objective, Epistatic, Rugged, and Neutral Fitness Landscapes}},
  booktitle                 = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'08)},
  editor                    = {Maarten Keijzer and Giuliano Antoniol and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Nikolaus Hansen and John H. Holmes and Gregory S. Hornby and Daniel Howard and James Kennedy and Sanjeev P. Kumar and Fernando G. Lobo and Julian Francis Miller and Jason H. Moore and Frank Neumann and Martin Pelikan and Jordan B. Pollack and Kumara Sastry and Kenneth Owen Stanley and Adrian Stoica and {El-Ghazali} Talbi and Ingo Wegener},
  publisher                 = {{ACM Press: {New York, NY, USA}}},
  pages                     = {795--802},
  year                      = {2008},
  location                  = {{Renaissance Atlanta Hotel Downtown: {Atlanta, GA, USA}}},
  url                       = {http://www.it-weise.de/documents/files/WNSRG2008GECCO.pdf},
  doi                       = {10.1145/1389095.1389252},
  key                       = {WNSRG2008ATMFMOERANFL},
},

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