Solving scheduling problem with time dependent learning effect to number of tardy jobs and range of lateness criteria

Abstract

In traditional scheduling problems, most literature assumes that the processing time of a job is fixed. However, there are many situations where the processing time of a job depends on the starting time or the position of the job in a sequence. In such situations, the actual processing time of a job may be more or less than its normal processing time if it is scheduled later. This phenomenon is known as the "learning effect''. In this study, we introduce a time-dependent learning effect into a single-machine scheduling problem. We consider the following objective function minimize range of lateness subject to the number of tardy jobs. A non-linear programming model is developed for the problem which belongs to NP-hard class. Also the model is tested on an example.