International audienceScheduling decisions in the diffusion and cleaning area of a semiconductor manufacturing facilityhave an important impact on the overall performance of a plant. Consequently, we wantto optimize those decisions while taking real-world constraints into account. An importantproperty of machines in this work area is their batching capability: They can perform multipleoperations at the same time. We want to take account of this in our algorithm.We need to schedule a given set of jobs. For each of them, a fixed sequence of operations mustbe performed. This sequence is called the route of the job. Operations can only be performed onqualified machines and their processing durations depend on the selected machine. A capacitylimit constrains the number of jobs that can be processed per batch. Each operation is assignedto a family and only operations of the same family can be combined in the same batch. Foreach job, we are given a ready date and a due date. Those constraints describe a flexiblejob-shop scheduling problem with batching. We aim to minimize total weighted tardiness.For the described problem, we present a simulated annealing algorithm that is based on anextended evaluation of disjunctive graphs. In our proposed approach, batching decisions aretaken dynamically during graph traversal
