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How the manufacturing system can be optimally controlled using this rule and its effects on the main performance measures of the system are also demonstrated. In addition, modeling such a simulation-based order acceptance rule is challenging and requires resolving many issues. This article discusses these issues. The lessons learned from this modeling experience are generic and can be used in similar contexts.<\/jats:p>","DOI":"10.1177\/0037549704045046","type":"journal-article","created":{"date-parts":[[2004,7,13]],"date-time":"2004-07-13T23:09:30Z","timestamp":1089760170000},"page":"131-142","source":"Crossref","is-referenced-by-count":22,"title":["Using Simulation to Make Order Acceptance\/Rejection Decisions"],"prefix":"10.1177","volume":"80","author":[{"given":"Amitava","family":"Nandi","sequence":"first","affiliation":[{"name":"BreconRidge Manufacturing Solutions 500 Palladium Drive, Kanata, Ontario, K2V 1C2, Canada,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul","family":"Rogers","sequence":"additional","affiliation":[{"name":"Department of Mechanical & Manufacturing Engineering 2500 University Drive N.W. 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