{
  "id": "0709.1020",
  "version": "v1",
  "published": "2007-09-07T08:41:06.000Z",
  "updated": "2007-09-07T08:41:06.000Z",
  "title": "Evolution Strategies in Optimization Problems",
  "authors": [
    "Pedro A. F. Cruz",
    "Delfim F. M. Torres"
  ],
  "comment": "Partially presented at the 5th Junior European Meeting on \"Control and Information Technology\" (JEM'06), Sept 20-22, 2006, Tallinn, Estonia. To appear in \"Proceedings of the Estonian Academy of Sciences -- Physics Mathematics\"",
  "journal": "Proc. Estonian Acad. Sci. Phys. Math., 2007, 56(4), 299--309",
  "categories": [
    "math.OC"
  ],
  "abstract": "Evolution Strategies are inspired in biology and part of a larger research field known as Evolutionary Algorithms. Those strategies perform a random search in the space of admissible functions, aiming to optimize some given objective function. We show that simple evolution strategies are a useful tool in optimal control, permitting to obtain, in an efficient way, good approximations to the solutions of some recent and challenging optimal control problems.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2007-09-07T08:41:06.000Z"
    }
  ],
  "analyses": {
    "subjects": [
      "49M99",
      "90C59",
      "68W20"
    ],
    "keywords": [
      "optimization problems",
      "challenging optimal control problems",
      "larger research field",
      "simple evolution strategies",
      "efficient way"
    ],
    "tags": [
      "journal article"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable",
      "adsabs": "2007arXiv0709.1020C"
    }
  }
}