A GA-Tabu algorithm for scheduling in-line steppers in low-yield scenarios

Abstract

This paper presents a scheduling algorithm for an in-line stepper in low-yield scenarios, which mostly appear in cases when new process/production is introduced. An in-line stepper is a bottleneck machine in a semiconductor fab. Its interior comprises a sequence of chambers, while its exterior is a dock equipped with several ports. The transportation unit for entry of each port is a job (a group of wafers), while that for each chamber is a piece of wafer. This transportation incompatibility may lead to a capacity-loss, in particular in low-yield scenarios. Such a capacity-loss could be alleviated by effective scheduling. The proposed scheduling algorithm, called GA-Tabu, is a combination of a genetic algorithm (GA) and a tabu search technique. Numerical experiments indicate that the GA-Tabu algorithm outperforms seven benchmark ones. In particular, the GA-Tabu algorithm outperforms a prior GA both in solution quality and computation efforts.