Single-machine and two-machine flowshop scheduling with general learning functions

Christos Koulamas

doi:10.1016/j.ejor.2006.01.030

2007-04-01

193

PRE

Christos Koulamas *

George J. Kyparisis

DOI：10.1016/j.ejor.2006.01.030

原文链接

原文求助

摘要

En 中文

We show that the O(n log n) (where n is the number of jobs) shortest processing time (SPT) sequence is optimal for the single-machine makespan and total completion time minimization problems when learning is expressed as a function of the sum of the processing times of the already processed jobs. We then show that the two-machine flowshop makespan and total completion time minimization problems are solvable by the SPT sequencing rule when the job processing times are ordered and job-position-based learning is in effect. Finally, we show that when the more specialized proportional job processing times are in place, then our flowshop results apply also in the more general sum-of-job-processing-times-based learning environment. (c) 2006 Elsevier B.V. All rights reserved.

Keyword:

scheduling

single machine

flowshop

shortest processing time

learning

optimal algorithms