{"product_id":"9781441951007","title":"International Series in Operations Research \u0026 Management Science","description":"\u003ch1\u003eInternational Series in Operations Research \u0026amp; Management Science\u003c\/h1\u003e \u003ch2\u003eGrassmann, Winfried K.\u003c\/h2\u003e \u003cp\u003eGreat advances have been made in recent years in the field of  computational probability. In particular, the state of the art  - as it relates to queuing systems, stochastic Petri-nets and  systems dealing with reliability - has benefited significantly  from these advances. The objective of this book is to make these  topics accessible to researchers, graduate students, and  practitioners. Great care was taken to make the exposition as clear as  possible. Every line in the book has been evaluated, and changes have  been made whenever it was felt that the initial exposition was not  clear enough for the intended readership. \u003cbr\u003e  The work of major research scholars in this field comprises the  individual chapters of \u003cem\u003eComputational Probability\u003c\/em\u003e. The first  chapter describes, in nonmathematical terms, the challenges in  computational probability. Chapter 2 describes the methodologies  available for obtaining the transition matrices for Markov chains,  with particular emphasis on stochastic Petri-nets. Chapter 3 discusses  how to find transient probabilities and transient rewards for these  Markov chains. The next two chapters indicate how to find steady-state  probabilities for Markov chains with a finite number of states. Both  direct and iterative methods are described in Chapter 4. Details of  these methods are given in Chapter 5. Chapters 6 and 7 deal with  infinite-state Markov chains, which occur frequently in queueing,  because there are times one does not want to set a bound for all  queues. Chapter 8 deals with transforms, in particular Laplace  transforms. The work of Ward Whitt and his collaborators, who have  recently developed a number of numerical methods for Laplace transform  inversions, is emphasized in this chapter. Finally, if one wants to  optimize a system, one way to do the optimization is through Markov  decision making, described in Chapter 9. Markov modeling has found  applications in many areas, three of which are described in detail:Chapter 10 analyzes discrete-time queues, Chapter 11 describes  networks of queues, and Chapter 12 deals with reliability theory.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2010-12-06\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9781441951007\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4757-4828-4\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 490\u003c\/p\u003e ","brand":"Springer US","offers":[{"title":"Default Title","offer_id":45378471198860,"sku":"9781441951007","price":215.1,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9781441951007.jpg?v=1770780449","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9781441951007","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}