Heuristic Search Algorithms for the Minimum Volume Ellipsoid

David L. Wood, David M Rocke

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


A method of robust estimation of multivariate location and shape that has attracted a lot of attention recently is Rousseeuw’s minimum volume ellipsoid estimator (MVE). This estimator has a high breakdown point but is difficult to compute successfully. In this article, we apply methods of heuristic search to this problem, including simulated annealing, genetic algorithms, and tabu search, and compare the results to the undirected random search algorithm that is often cited. Heuristic search provides several effective algorithms that are far more computationally efficient than random search. Furthermore, random search, as currently implemented, is shown to be ineffective for larger problems.

Original languageEnglish (US)
Pages (from-to)69-95
Number of pages27
JournalJournal of Computational and Graphical Statistics
Issue number1
StatePublished - 1993


  • Breakdown point
  • Genetic algorithms
  • Multivariate location and shape
  • Robust estimation
  • Simulated annealing
  • Tabu search

ASJC Scopus subject areas

  • Discrete Mathematics and Combinatorics
  • Statistics and Probability
  • Statistics, Probability and Uncertainty


Dive into the research topics of 'Heuristic Search Algorithms for the Minimum Volume Ellipsoid'. Together they form a unique fingerprint.

Cite this