{"citation":{"chicago":"Sosa, Hernández V, O Schütze, G Rudolph, and Heike Trautmann. “The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume.” In <i>EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV</i>, edited by M Emmerich, A Deutz, O Schuetze, T Bäck, A Tantar, PD Moral, P Legrand, P Bouvry, and CA Coello, 227:189–205. Advances in Intelligent Systems and Computing. Springer International Publishing, 2013. <a href=\"https://doi.org/10.1007/978-3-319-01128-8_13\">https://doi.org/10.1007/978-3-319-01128-8_13</a>.","mla":"Sosa, Hernández V., et al. “The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume.” <i>EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV</i>, edited by M Emmerich et al., vol. 227, Springer International Publishing, 2013, pp. 189–205, doi:<a href=\"https://doi.org/10.1007/978-3-319-01128-8_13\">10.1007/978-3-319-01128-8_13</a>.","short":"H.V. Sosa, O. Schütze, G. Rudolph, H. Trautmann, in: M. Emmerich, A. Deutz, O. Schuetze, T. Bäck, A. Tantar, P. Moral, P. Legrand, P. Bouvry, C. Coello (Eds.), EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV, Springer International Publishing, 2013, pp. 189–205.","ieee":"H. V. Sosa, O. Schütze, G. Rudolph, and H. Trautmann, “The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume,” in <i>EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV</i>, vol. 227, M. Emmerich, A. Deutz, O. Schuetze, T. Bäck, A. Tantar, P. Moral, P. Legrand, P. Bouvry, and C. Coello, Eds. Springer International Publishing, 2013, pp. 189–205.","apa":"Sosa, H. V., Schütze, O., Rudolph, G., &#38; Trautmann, H. (2013). The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume. In M. Emmerich, A. Deutz, O. Schuetze, T. Bäck, A. Tantar, P. Moral, P. Legrand, P. Bouvry, &#38; C. Coello (Eds.), <i>EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV</i> (Vol. 227, pp. 189–205). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-319-01128-8_13\">https://doi.org/10.1007/978-3-319-01128-8_13</a>","bibtex":"@inbook{Sosa_Schütze_Rudolph_Trautmann_2013, series={Advances in Intelligent Systems and Computing}, title={The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume}, volume={227}, DOI={<a href=\"https://doi.org/10.1007/978-3-319-01128-8_13\">10.1007/978-3-319-01128-8_13</a>}, booktitle={EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV}, publisher={Springer International Publishing}, author={Sosa, Hernández V and Schütze, O and Rudolph, G and Trautmann, Heike}, editor={Emmerich, M and Deutz, A and Schuetze, O and Bäck, T and Tantar, A and Moral, PD and Legrand, P and Bouvry, P and Coello, CA}, year={2013}, pages={189–205}, collection={Advances in Intelligent Systems and Computing} }","ama":"Sosa HV, Schütze O, Rudolph G, Trautmann H. The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume. In: Emmerich M, Deutz A, Schuetze O, et al., eds. <i>EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV</i>. Vol 227. Advances in Intelligent Systems and Computing. Springer International Publishing; 2013:189–205. doi:<a href=\"https://doi.org/10.1007/978-3-319-01128-8_13\">10.1007/978-3-319-01128-8_13</a>"},"type":"book_chapter","publisher":"Springer International Publishing","status":"public","_id":"46385","user_id":"15504","year":"2013","editor":[{"last_name":"Emmerich","full_name":"Emmerich, M","first_name":"M"},{"first_name":"A","full_name":"Deutz, A","last_name":"Deutz"},{"last_name":"Schuetze","full_name":"Schuetze, O","first_name":"O"},{"first_name":"T","last_name":"Bäck","full_name":"Bäck, T"},{"first_name":"A","last_name":"Tantar","full_name":"Tantar, A"},{"first_name":"PD","last_name":"Moral","full_name":"Moral, PD"},{"last_name":"Legrand","full_name":"Legrand, P","first_name":"P"},{"full_name":"Bouvry, P","last_name":"Bouvry","first_name":"P"},{"first_name":"CA","full_name":"Coello, CA","last_name":"Coello"}],"publication":"EVOLVE — A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV","page":"189–205","language":[{"iso":"eng"}],"volume":227,"department":[{"_id":"34"},{"_id":"819"}],"date_created":"2023-08-04T15:37:00Z","doi":"10.1007/978-3-319-01128-8_13","publication_identifier":{"isbn":["978-3-319-01127-1"]},"author":[{"first_name":"Hernández V","last_name":"Sosa","full_name":"Sosa, Hernández V"},{"last_name":"Schütze","full_name":"Schütze, O","first_name":"O"},{"full_name":"Rudolph, G","last_name":"Rudolph","first_name":"G"},{"last_name":"Trautmann","full_name":"Trautmann, Heike","id":"100740","first_name":"Heike","orcid":"0000-0002-9788-8282"}],"title":"The Directed Search Method for Pareto Front Approximations with Maximum Dominated Hypervolume","abstract":[{"text":"In many applications one is faced with the problem that multiple objectives have to be optimized at the same time. Since typically the solution set of such multi-objective optimization problems forms a manifold which cannot be computed analytically, one is in many cases interested in a suitable finite size approximation of this set. One widely used approach is to find a representative set that maximizes the dominated hypervolume that is defined by the images in objective space of these solutions and a given reference point.\r\n\r\nIn this paper, we propose a new point-wise iterative search procedure, Hypervolume Directed Search (HVDS), that aims to increase the hypervolume of a given point in an archive for bi-objective unconstrained optimization problems. We present the HVDS both as a standalone algorithm and as a local searcher within a specialized evolutionary algorithm. Numerical results confirm the strength of the novel approach.","lang":"eng"}],"series_title":"Advances in Intelligent Systems and Computing","intvolume":"       227","date_updated":"2023-10-16T13:44:50Z"}