Mathematical Programming based Heuristics for Scheduling the General Batch Plant

In this paper we present heuristic strategies for scheduling the generalized batch processing plant. These heuristics use a mixed integer linear programming (MILP) formulation of the scheduling problem and are based on employing different modifications to the exact solution procedure to efficiently obtain sub-optimal solutions to the problem. All of these heuristics exploit the structure of the scheduling problem and consist of an initial phase that identifies a feasible schedule and a final phase that improves upon this schedule. The quality of these heuristics has been experimentally tested on a number of case studies. The computational effort required was only a small fraction of that of the exact procedure and the solutions obtained by the most effective heuristics were consistently close to the optimum.