COMPLETION-TIME ALGORITHMS FOR SERIAL MULTIPRODUCT BATCH PROCESSES WITH SHARED STORAGE

Scheduling in batch processes with constrained resources is a very complex but important problem. In this paper, we consider intermediate storage as a representative constrained resource and study an important subproblem in the scheduling of serial multiproduct batch plants, namely the determination of a timetable for a given sequence of production so as to minimize makespan. We show that in the presence of storage, this becomes a complex problem, and its optimal solution seems intractable. We propose a strategy for assigning storage based on the priorities of products in the production sequence, and show its superiority over the first-come first-serve type of strategy. Using this strategy, we develop a new and efficient completion time algorithm for determining very good schedules for batch plants with arbitrarily constrained shared, finite storage. In the process, we also highlight several interesting issues in dealing with constrained resources in general and propose strategies related to their avail ability and efficient utilization. Numerical evaluation on systems with a specific storage policy shows the superiority of our algorithms over a literature algorithm. By studying a specific resource, this paper represents a significant step towards the development of systematic methods for batch process scheduling with constrained resources. © 1990.