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

Chie Wun Chiou, Muh-Cherng Wu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

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.

Original languageEnglish
Pages (from-to)11925-11933
Number of pages9
JournalExpert Systems with Applications
Volume36
Issue number9
DOIs
StatePublished - 1 Nov 2009

Keywords

  • Flow shop
  • Genetic algorithm
  • Meta-heuristic algorithm
  • Port capacity constraints
  • Scheduling
  • Semiconductor
  • Tabu search

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