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In this paper, the application of continuous-domain genetic algorithms (GAs) is proposed in order to support the optimization process of resource reflow in the network channels. GAs allow one to perform simulation-based optimization and provide desirable operating conditions in the face of a priori unknown, time-varying demand. The effectiveness of inventory management process governed under an order-up-to policy involves two different objectives\u2014holding costs and service level. Using the network analytical model with the inventory management policy implemented in a centralized way, GAs search a space of candidate solutions to find optimal policy parameters for a given topology. Numerical experiments confirm the analytical assumptions.<\/jats:p>","DOI":"10.3390\/data3040068","type":"journal-article","created":{"date-parts":[[2018,12,18]],"date-time":"2018-12-18T02:15:59Z","timestamp":1545099359000},"page":"68","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Continuous Genetic Algorithms as Intelligent Assistance for Resource Distribution in Logistic Systems"],"prefix":"10.3390","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3438-0174","authenticated-orcid":false,"given":"\u0141ukasz","family":"Wieczorek","sequence":"first","affiliation":[{"name":"Institute of Information Technology, Lodz University of Technology, 90-924 \u0141\u00f3d\u017a, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4420-9941","authenticated-orcid":false,"given":"Przemys\u0142aw","family":"Ignaciuk","sequence":"additional","affiliation":[{"name":"Institute of Information Technology, Lodz University of Technology, 90-924 \u0141\u00f3d\u017a, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Gereffi, G., and Frederick, S. 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