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. © 2006 Elsevier Ltd. All rights reserved.
Zhenya Jia, Marianthi G. Ierapetritou