By Gediminas Adomavicius, Alok Gupta
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Das Buch vermittelt einen umfassenden ? berblick ? ber Modelle und Algorithmen zur dynamischen Losgr? ?enoptimierung f? r ein- und mehrstufige Erzeugnisstrukturen, die eingehend erl? utert und anhand zahlreicher Beispiele veranschaulicht werden. Au? erdem werden Verfahren zur optimalen Bestellmengenplanung und Lieferantenauswahl unter Beachtung von Mengenrabatten dargestellt.
To keep up competitiveness within the rising international financial system, U. S. production needs to upward thrust to new criteria of product caliber, responsiveness to clients, and method flexibility. This quantity offers a concise and well-organized research of latest study instructions to accomplish those targets. 5 severe parts obtain in-depth research of current practices, wanted development, and examine priorities: complex engineered fabrics that provide the possibility of higher life-cycle functionality and different earnings; gear reliability and upkeep practices for higher returns on capital funding; quick product attention concepts to hurry supply to undefined; clever production regulate for more suitable reliability and bigger precision; and development a group with the multidisciplinary talents wanted for competitiveness.
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Personalization: The State of the Art and Future Directions 31 Examples of such customized offerings include customized jeans, shoes, CD records and personal computers. It does not require any manufacturing and only needs to deal with the selection and conﬁgurability issues, such as selection of appropriate books to display on a website or generation of personalized web pages and other online content. Such customization can be done in real time with negligible costs. Although both problems are important, we will focus on the latter one in the rest of this section since the ﬁrst one is a large subject on its own and can constitute a separate stand-alone paper.
For example, a marketing manager may specify the following business rule: if a consumer of a certain type visits the online grocery store on a Sunday night, then this consumer should be shown the discount coupons for diapers. , 1995; Resnick et al, 1994; Shardanand and Maes, 1995).
Overeager personalizers: These applications have poor proﬁles but make proactive targeting of its offerings. This can often lead to poor results because of the limited information about consumers and faulty assumptions about their preferences. Examples of these types of applications include recommending books similar to the ones the consumer bought recently and various types of baby products to a woman who recently had a miscarriage. Smart personalizers: These applications use rich proﬁles and provide proactive targeting of the offerings.
Business Computing, Volume 3 by Gediminas Adomavicius, Alok Gupta