02979nam a22004935i 4500001001800000003000900018005001700027007001500044008004100059020001800100020001900118024003100137040000900168082001200177100003000189245013500219264004600354300003300400336002600433337002600459338003900485347002400524490006700548505061000615520061101225650001701836650002001853650003901873650002801912650002801940650001701968650002901985650004902014650004102063650004302104650002802147700002802175700002602203710003402229773002002263776003602283830006702319856009902386978-0-387-27615-1DE-He21320260521091844.0cr nn 008mamaa100301s2005    xxu|    s    |||| 0|eng d  a9780387276151  a997803872761517 a10.1007/0-387-27615-72doi  cCICY04a5192231 aSethi, Suresh P.eauthor.10aAverage-Cost Control of Stochastic Manufacturing Systemsh[recurso electrónico] /cby Suresh P. Sethi, Hanqin Zhang, Qing Zhang. 1aNew York, NY :bSpringer New York,c2005.  aXV, 324 p.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  arecurso en líneabcr2rdacarrier  atext filebPDF2rda1 aStochastic Modelling and Applied Probability,x0172-4568 ;v540 aand Models of Manufacturing Systems -- Concept of Near-Optimal Control -- Models of Manufacturing Systems -- Optimal Control of Manufacturing Systems: Existence and Characterization -- Optimal Control of Parallel-Machine Systems -- Optimal Control of Dynamic Flowshops -- Optimal Controls of Dynamic Jobshops -- Risk-Sensitive Control -- Near-Optimal Controls -- Near-Optimal Control of Parallel-Machine Systems -- Near-Optimal Control of Dynamic Flowshops -- Near-Optimal Controls of Dynamic Jobshops -- Near-Optimal Risk-Sensitive Control -- Conclusions -- Further Extensions and Open Research Problems.  aThis book is concerned with hierarchical control of manufacturing systems under uncertainty. It focuses on system performance measured in long-run average cost criteria, exploring the relationship between control problems with a discounted cost and that with a long-run average cost in connection with hierarchical control. A new theory is articulated that shows that hierarchical decision making in the context of a goal-seeking manufacturing system can lead to a near optimization of its objective. The approach in the book considers manufacturing systems in which events occur at different time scales.  0aMATHEMATICS. 0aSYSTEMS THEORY. 0aDISTRIBUTION (PROBABILITY THEORY). 0aMECHANICAL ENGINEERING. 0aINDUSTRIAL ENGINEERING.14aMATHEMATICS.24aSYSTEMS THEORY, CONTROL.24aPROBABILITY THEORY AND STOCHASTIC PROCESSES.24aOPERATIONS RESEARCH/DECISION THEORY.24aINDUSTRIAL AND PRODUCTION ENGINEERING.24aMECHANICAL ENGINEERING.1 aZhang, Hanqin.eauthor.1 aZhang, Qing.eauthor.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9780387219479 0aStochastic Modelling and Applied Probability,x0172-4568 ;v5440uhttp://dx.doi.org/10.1007/0-387-27615-7zVer el texto completo en las instalaciones del CICY