Concepts of forecast and decision horizons: applications to dynamic stochastic optimization problems
Mathematics of Operations Research
A weakly monotonic backward induction algorithm on finite bounded subsets of vector lattices
Journal of Computational and Applied Mathematics - Special Issue: Proceedings of the 10th international congress on computational and applied mathematics (ICCAM-2002)
Computers & Mathematics with Applications
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Forecast horizons are defined as long enough planning horizons that ensure agreement of first period optimal production decisions of finite and infinite horizon problems regardless of changes in future demand. In this paper, we prove forecast horizon existence and provide computational procedures for production planning problems that satisfy the following monotonicity property: for any fixed finite planning horizon, there exist first period optimal solutions that are monotone with respect to monotone changes in stochastic demand.