{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T11:36:33Z","timestamp":1777548993264,"version":"3.51.4"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"abstract":"<jats:p>This paper proposes a discrete-event model of a multi-product (r, Q) inventory control system. The described approach provides a computationally efficient method to estimate a current inventory policy and test alternatives. In the considered model, values of the reorder level r and the reorder quantity Q are approached through iterative methods. The modeled inventory system operates under stochastic demand and lead time. Besides, the limited storage capacity is allocated among several products. Unfulfilled demand is interpreted as a lost opportunity and no backlog shall be fulfilled later. Generally, the inventory control system under consideration may be classified as an extended &amp;ldquo;base stock&amp;rdquo; with a common storage resource. The paper includes the mathematical description, the simulation algorithm and the numerical example of the model of the three-product (r, Q) inventory control system with detailed risk and reliability analysis.<\/jats:p>","DOI":"10.3233\/978-1-61499-933-1-32","type":"book-chapter","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:06:08Z","timestamp":1740053168000},"source":"Crossref","is-referenced-by-count":1,"title":["The Discrete-Event Approach to Simulate Stochastic Multi-Product (r, Q) Inventory Control Systems"],"prefix":"10.3233","author":[{"family":"Jackson Ilya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Tolujevs Jurijs","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Information Modelling and Knowledge Bases XXX"],"original-title":[],"deposited":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:28:53Z","timestamp":1740054533000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-932-4&spage=32&doi=10.3233\/978-1-61499-933-1-32"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-933-1-32","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2019]]}}}