A hybrid genetic algorithm for flowshop lot streaming with setups and variable sublots

Abstract

Lot streaming is the process of splitting a given lot or job to allow the overlapping of successive operations in flowshops or multi-stage manufacturing systems to reduce manufacturing lead time. Recent literature shows that significant lead time improvement is possible if variable sublots, instead of equal or consistent sublots, are used when production setup time is considered. However, lot streaming problems with variable sublots are difficult to solve to optimality using off-shelf optimisation packages even for problems of small and experimental sizes. Thus, efficient solution procedures are needed for solving such problems for practical applications. In this paper, we develop a mathematical programming model and a hybrid genetic algorithm for solving n-job m-machine lot streaming problems with variable sublots considering setup times. The preliminary computational results are encouraging.

Keywords:

• lot streaming
• variable sublots
• hybrid genetic algorithm

Acknowledgements

This research is supported by Discovery Grant from NSERC of Canada and by Faculty Research Support Fund from the Faculty of Engineering and Computer Science, Concordia University, Montreal, Quebec, Canada. We also thank the anonymous referees for their thorough reviews on an early version of this paper.