2170 11 59555 2 166027 document 59555 RR-84-05.pdf application/pdf cbaf7a446d1e8f017ec420e1eb029b50 MD5 4343459 2016-06-02 09:14:47 https://pure.iiasa.ac.at/id/eprint/2170/1/RR-84-05.pdf 2170 1 1 application/pdf text en public cc_by

RR-84-05.pdf

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/59555 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/59555 http://eprints.org/relation/isIndexCodesVersionOf https://pure.iiasa.ac.at/id/document/59555 archive 351 disk0/00/00/21/70 2016-01-15 01:52:53 2021-08-27 17:35:26 2016-01-15 01:52:53 monograph show 1 Dempster M.A.H. AL0086 Fisher M.L. Jansen L. Lageweg B.J. Lenstra J.K. Rinnooy Kan A.H.G. pub iis_met prog_sds Certain multistage decision problems that arise frequently in operations management planning and control allow a natural formulation as multistage stochastic programs. In job shop scheduling, for example, the first stage could correspond to the acquisition of resources subject to probabilistic information about the jobs to be processed, and the second stage to the actual allocation of the resources to the jobs given deterministic information about their processing requirements. For two simple versions of this two-stage hierarchical scheduling problem, we describe heuristic solution methods and show that their performance is asymptotically optimal both in expectation and in probability. 1983 published RR-84-005. Reprinted from Mathematics of Operations Research, 8(4):525-537 [1983]. RP-84-005 Reprinted from Mathematics of Operations Research; 8(4):525-537 [1983] 10 1829 public research_reprint Mathematics of Operations Research 8 4 IIASA, Laxenburg, Austria 525-537 16 TRUE FALSE info:eu-repo/semantics/book