{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T00:23:27Z","timestamp":1776471807342,"version":"3.51.2"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319314709","type":"print"},{"value":"9783319314716","type":"electronic"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-31471-6_5","type":"book-chapter","created":{"date-parts":[[2016,3,19]],"date-time":"2016-03-19T02:35:28Z","timestamp":1458354928000},"page":"58-70","source":"Crossref","is-referenced-by-count":3,"title":["Quasi-random Numbers Improve the CMA-ES on the BBOB Testbed"],"prefix":"10.1007","author":[{"given":"Olivier","family":"Teytaud","sequence":"first","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,3,20]]},"reference":[{"key":"5_CR1","series-title":"Natural Computing Series","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-04378-3","volume-title":"The Theory of Evolution Strategies","author":"HG Beyer","year":"2001","unstructured":"Beyer, H.G.: The Theory of Evolution Strategies. Natural Computing Series. Springer, Heideberg (2001)"},{"key":"5_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/978-3-540-87700-4_13","volume-title":"Parallel Problem Solving from Nature \u2013 PPSN X","author":"H-G Beyer","year":"2008","unstructured":"Beyer, H.-G., Sendhoff, B.: Covariance matrix adaptation revisited \u2013 the CMSA evolution strategy. In: Rudolph, G., Jansen, T., Lucas, S., Poloni, C., Beume, N. (eds.) PPSN 2008. LNCS, vol. 5199, pp. 123\u2013132. springer, Heidelberg (2008)"},{"key":"5_CR3","unstructured":"Chaslot, G., Hoock, J.B., Teytaud, F., Teytaud, O.: On the huge benefit of quasi-random mutations for multimodal optimization with application to grid-based tuning of neurocontrollers. In: ESANN (2009). http:\/\/dblp.uni-trier.de\/db\/conf\/esann\/esann2009.html#ChaslotHTT09"},{"key":"5_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1007\/11844297_4","volume-title":"Parallel Problem Solving from Nature - PPSN IX","author":"O Teytaud","year":"2006","unstructured":"Teytaud, O., Gelly, S., Mary, J.: On the ultimate convergence rates for isotropic algorithms and the best choices among various forms of isotropy. In: Runarsson, T.P., Beyer, H.-G., Burke, E.K., Merelo-Guerv\u00f3s, J.J., Whitley, L.D., Yao, X. (eds.) PPSN 2006. LNCS, vol. 4193, pp. 32\u201341. Springer, Heidelberg (2006)"},{"key":"5_CR5","first-page":"429","volume":"37","author":"A Georgieva","year":"2010","unstructured":"Georgieva, A., Jordanov, I.: A hybrid meta-heuristic for global optimisation using low-discrepancy sequences of points. Comput. Oper. Res. Spec. Issue Hybrid Metaheuristics 37, 429 (2010)","journal-title":"Comput. Oper. Res. Spec. Issue Hybrid Metaheuristics"},{"key":"5_CR6","unstructured":"Hansen, N., Ostermeier, A.: Adapting arbitrary normal mutation distributions in evolution strategies: the covariance matrix adaption. In: Proceedings of the IEEE Conference on Evolutionary Computation (CEC 1996), pp. 312\u2013317. IEEE Press (1996)"},{"issue":"1","key":"5_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/106365603321828970","volume":"11","author":"N Hansen","year":"2003","unstructured":"Hansen, N., Ostermeier, A.: Completely derandomized self-adaptation in evolution strategies. Evol. Comput. 11(1), 1 (2003)","journal-title":"Evol. Comput."},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Kimura, S., Matsumura, K.: Genetic algorithms using low-discrepancy sequences. In: GECCO, pp. 1341\u20131346 (2005)","DOI":"10.1145\/1068009.1068225"},{"key":"5_CR9","doi-asserted-by":"crossref","unstructured":"Lindemann, S.R., LaValle, S.M.: Incremental low-discrepancy lattice methods for motion planning. In: Proceedings IEEE International Conference on Robotics and Automation, pp. 2920\u20132927 (2003)","DOI":"10.1109\/ROBOT.2003.1242039"},{"issue":"3","key":"5_CR10","first-page":"435","volume":"10","author":"M Mascagni","year":"2004","unstructured":"Mascagni, M., Chi, H.: On the scrambled halton sequence. Monte-Carlo Methods Appl. 10(3), 435\u2013442 (2004)","journal-title":"Monte-Carlo Methods Appl."},{"key":"5_CR11","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611970081","volume-title":"Random Number Generation and Quasi-Monte-Carlo Methods","author":"H Niederreiter","year":"1992","unstructured":"Niederreiter, H.: Random Number Generation and Quasi-Monte-Carlo Methods. Society of Industrial and Applied Mathematics, Philadelphia (1992)"},{"key":"5_CR12","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/0022-314X(88)90025-X","volume":"30","author":"H Niederreiter","year":"1988","unstructured":"Niederreiter, H.: Low-discrepancy and low-dispersion sequences. J. Number Theor. 30, 51 (1988)","journal-title":"J. Number Theor."},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Owen, A.: Multidimensional variation for quasi-Monte-Carlo (2004)","DOI":"10.1142\/9789812567765_0004"},{"issue":"5","key":"5_CR14","doi-asserted-by":"publisher","first-page":"790","DOI":"10.1137\/0716058","volume":"16","author":"IM Sobol","year":"1979","unstructured":"Sobol, I.M.: On the systematic search in a hypercube. SIAM J. Numer. Anal. 16(5), 790\u2013793 (1979)","journal-title":"SIAM J. Numer. Anal."},{"key":"5_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1007\/978-3-540-87700-4_33","volume-title":"Parallel Problem Solving from Nature \u2013 PPSN X","author":"O Teytaud","year":"2008","unstructured":"Teytaud, O.: When does quasi-random work? In: Rudolph, G., Jansen, T., Lucas, S., Poloni, C., Beume, N. (eds.) PPSN 2008. LNCS, vol. 5199, pp. 325\u2013336. Springer, Heidelberg (2008). http:\/\/dblp.uni-trier.de\/db\/conf\/ppsn\/ppsn2008.html#Teytaud08"},{"key":"5_CR16","unstructured":"Teytaud, O., Gelly, S.: DCMA, yet another derandomization in covariance-matrix-adaptation. In: D. Thierens et al. (ed.) GECCO, pp. 955\u2013922. London Royaume-Uni (2007). http:\/\/hal.inria.fr\/inria-00173207\/en\/"},{"key":"5_CR17","series-title":"Lecture Notes in Statistics","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1007\/978-1-4612-1690-2_30","volume-title":"Monte Carlo and Quasi-Monte Carlo Methods 1996","author":"B Tuffin","year":"1997","unstructured":"Tuffin, B.: A new permutation choice in halton sequences. In: Niederreiter, H., Hellekalek, P., Larcher, G., Zinterhof, P., et al. (eds.) Monte Carlo and Quasi-Monte Carlo Methods 1996. Lecture Notes in Statistics, vol. 127, pp. 427\u2013435. Springer, New York (1997)"},{"issue":"1, 2","key":"5_CR18","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1016\/j.cam.2005.05.022","volume":"189","author":"B Vandewoestyne","year":"2006","unstructured":"Vandewoestyne, B., Cools, R.: Good permutations for deterministic scrambled halton sequences in terms of l2-discrepancy. Comput. Appl. Math. 189(1, 2), 341\u2013361 (2006)","journal-title":"Comput. Appl. Math."},{"key":"5_CR19","doi-asserted-by":"publisher","first-page":"887","DOI":"10.1016\/S0895-7177(00)00178-3","volume":"32","author":"X Wang","year":"2000","unstructured":"Wang, X., Hickernell, F.: Randomized halton sequences. Math. Comput. Model. 32, 887\u2013899 (2000)","journal-title":"Math. Comput. Model."},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Warnock, T.: Computational investigations of low-discrepancy point sets. In: Zaremba, S.K. (ed.) Applications of Number Theory to Numerical Analysis (Proceedings of the Symposium), University of Montreal, pp. 319\u2013343 (1972)","DOI":"10.1016\/B978-0-12-775950-0.50015-7"},{"key":"5_CR21","series-title":"Lecture Notes in Statistics","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1007\/978-1-4612-2552-2_23","volume-title":"Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing","author":"TT Warnock","year":"1995","unstructured":"Warnock, T.T.: Computational investigations of low-discrepancy point sets II. In: Niederreiter, H., Shiue, P.J.-S. (eds.) Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing. Lecture Notes in Statistics, vol. 106, pp. 354\u2013361. Springer, New York (1995)"}],"container-title":["Lecture Notes in Computer Science","Artificial Evolution"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-31471-6_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T21:16:02Z","timestamp":1748812562000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-31471-6_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319314709","9783319314716"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-31471-6_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016]]}}}