{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T15:57:59Z","timestamp":1784563079466,"version":"3.55.0"},"reference-count":28,"publisher":"SAGE Publications","issue":"7","license":[{"start":{"date-parts":[[2014,6,9]],"date-time":"2014-06-09T00:00:00Z","timestamp":1402272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["SIMULATION"],"published-print":{"date-parts":[[2014,7]]},"abstract":"<jats:p>This article introduces a stand-alone implementation of the quantized state system (QSS) integration methods for continuous and hybrid system simulation. QSS methods replace the time discretization of classic numerical integration by the quantization of the state variables. These algorithms lead to discrete event approximations of the original continuous systems and show some advantages over classic numerical integration schemes.<\/jats:p>\n                  <jats:p>For simplicity, most implementations of QSS methods were confined to discrete event simulation engines. The problem is that they were not fully efficient, as they wasted much of the computational load in the discrete event simulation mechanism. The stand-alone QSS solver presented here overcomes this problem, improving in more than one order of magnitude the computation times of the previous discrete event implementations.<\/jats:p>\n                  <jats:p>Besides describing the solver structure and functionality, the article analyzes four different models and compares the performance of the new solver with that of the discrete event implementation, and with that of different classic solvers.<\/jats:p>","DOI":"10.1177\/0037549714536255","type":"journal-article","created":{"date-parts":[[2014,6,10]],"date-time":"2014-06-10T03:20:49Z","timestamp":1402370449000},"page":"782-799","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":36,"title":["A stand-alone quantized state system solver for continuous system simulation"],"prefix":"10.1177","volume":"90","author":[{"given":"Joaqu\u00edn","family":"Fern\u00e1ndez","sequence":"first","affiliation":[{"name":"CIFASIS\u2013CONICET, FCEIA, UNR, Rosario, Argentina"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ernesto","family":"Kofman","sequence":"additional","affiliation":[{"name":"CIFASIS\u2013CONICET, FCEIA, UNR, Rosario, Argentina"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2014,6,9]]},"reference":[{"key":"e_1_3_3_2_2","volume-title":"Solving Ordinary Dfferential Equations I. 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