Enterprise-wide supply chain planning problems naturally exhibit a multi-level decision network structure, where for example, one level may correspond to a local plant control/scheduling/planning problem and another level to a corresponding plant-wide planning/network problem. Such a multi-level decision network structure can be mathematically represented by using multi-level programming principles. In this paper, we specifically address bilevel decision-making problems under uncertainty in the context of enterprise-wide supply chain optimization with one level corresponding to a plant planning problem, while the other to a distribution network problem. We first describe how such problems can be modelled as bilevel programming problems and then we present an effective solution strategy based on parametric programming techniques. An attractive feature of the proposed strategy is the fact that it transforms the bilevel problem into a family of single parametric optimization problems, which can be solved to global optimality. A numerical example is presented to illustrate the proposed framework. (C) 2003 Elsevier Ltd. All rights reserved.