A framework for the probabilistic analysis of hierarchical planning systems |
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Authors: | J. K. Lenstra A. H. G. Rinnooy Kan L. Stougie |
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Affiliation: | (1) Centre for Mathematics and Computer Science, Kruislaan 413, NL-1098 SJ Amsterdam, The Netherlands;(2) Erasmus University, P.O. Box 1738, NL-3000 DR Rotterdam, The Netherlands;(3) Centre for Mathematics and Computer Science, Kruislaan 413, NL-1098 SJ Amsterdam, The Netherlands |
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Abstract: | ![]() As we have argued in previous papers, multi-level decision problems can often be modeled as multi-stage stochastic programs, and hierarchical planning systems designed for their solution, when viewed as stochastic programming heuristics, can be subjected to analytical performance evaluation. The present paper gives a general formulation of such stochastic programs and provides a framework for the design and analysis of heuristics for their solution. The various ways to measure the performance of such heuristics are reviewed, and some relations between these measures are derived. Our concepts are illustrated on a simple two-level planning problem of a general nature and on a more complicated two-level scheduling problem. |
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Keywords: | Hierarchical planning problem stochastic programming heuristic performance measure probabilistic analysis asymptotic optimality machine scheduling |
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