Scheduling jobs with general learning functions

This paper deals with single-machine scheduling problems with a more general learning effect based on sum-of-processing-time. In this study, sum-of-processing-time-based learning effect means that the processing time of a job is defined by a decreasing function of the total normal processing time of jobs that come before it in the sequence. Results show that even with the introduction of the sum-of-processing-time-based learning effect to job processing times, single-machine makespan minimization problems remain polynomially solvable. The curves of the optimal schedule of a total completion time minimization problem are V-shaped with respect to job normal processing times.