Dempster, M. A. H.; Fisher, M. L.; Jansen, L.; Lageweg, B. J.; Lenstra, J. K.; Rinnooy Kan, A. H. G. Analysis of heuristics for stochastic programming: Results for hierarchical scheduling problems. (English) Zbl 0532.90078 Math. Oper. Res. 8, 525-537 (1983). Summary: 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. Cited in 1 ReviewCited in 15 Documents MSC: 90C15 Stochastic programming 90B35 Deterministic scheduling theory in operations research Keywords:asymptotic optimality; multistage decision problems; multistage stochastic programs; job shop scheduling; two-stage hierarchical scheduling; heuristic solution methods PDFBibTeX XMLCite \textit{M. A. H. Dempster} et al., Math. Oper. Res. 8, 525--537 (1983; Zbl 0532.90078) Full Text: DOI Link