A scatter search approach for general flowshop scheduling problem

Abstract

This paper proposes a new evolutionary technique called scatter search for scheduling problems of a general flow-shop. Scatter search (SS) is applied to this problem as it is able to provide a wide exploration of the search space through intensification and diversification. In addition it has a unifying principle for joining solutions which exploit the adaptive memory principle to avoid generating or incorporating duplicate solutions at various stages of the problem. This methodology provides substantially better results than the Tabu search approach of Nowicki and Smutnicki (Manage Sci 42(6):797–813, 1996) and Jain and Meeran (Comput Oper Res 29:1873–1901, 2002). The proposed framework achieves an average deviation of 14.25% from the lower bound solution of benchmark problems of Demirkol et al. (Eur J Oper Res 109(1):137–141, 1998), while the scatter search technique gives the best solutions for 32 of 40 of their benchmark problems.