The problem of short-term scheduling under uncertainty is addressed in this paper through a multiobjective optimization framework that incorporates economic expectation, robustness, and flexibility in terms of demand satisfaction. In order to be able to identify Pareto optimal solutions, a new approach is applied which is based on normal boundary intersection (NBI) technique. The main advantage of this technique is that it avoids the selection of arbitrary parameters and generates a set of evenly distributed set of points independent of the scales of the objectives. Utilizing this idea, alternative schedules are generated that represent trade-off between the various objectives in the face of uncertainty. The approach is illustrated through three case studies and the special characteristics of the scheduling problems are discussed. (c) 2006 Elsevier Ltd. All rights reserved.