Flexible solutions in disjunctive scheduling: General formulation and study of the flow-shop case

We consider the context of decision support for schedule modification after the computation off-line of a predictive optimal (or near optimal) schedule. The purpose of this work is to provide the decision-maker a characterization of possible modifications of the predictive schedule while preserving optimality. In the context of machine scheduling, the anticipated modifications are changes in the predictive order of operations on the machines. To achieve this goal, a flexible solution feasible w.r.t to operations deadlines, is provided instead of a single predictive schedule. A flexible solution represents a set of semi-active schedules and is characterized by a partial order on each machine, so that the total order can be set on-line, as required by the decision maker. A flexible solution is feasible if all the complete schedules that can be obtained by extension are also feasible. In this paper we develop two main issues. The first one concerns the evaluation of a flexible solution in the worst case allowing to certify if the solution is feasible. The second issue is the computation of feasible (w.r.t deadlines) flexible solutions of maximal flexibility imposed by the decision maker. Under an epsilon-constraint framework, solving this problem allows to find compromise solutions for the flexibility criterion and any minmax regular scheduling criterion. The special case of the flow-shop scheduling problem is studied and computational experiments are carried out.