Single machine scheduling with autonomous learning and induced learning

• Both autonomous and induced learning are considered in single-machine scheduling.
• Specialized time intervals are reserved to implement induced learning activities.
• Optimal job sequence is determined.
• Algorithms are provided to get the optimal position of induced learning activities.

As an important management tool of winning competitive advantage, induced learning effect has been widely studied in empirical research area. But it is hardly considered in scheduling problems. In this paper, autonomous and induced learning are both taken into consideration. The investment of induced learning is interpreted as specialized time intervals to implement training, knowledge sharing and transferring etc. We present algorithms to determine jointly the optimal job sequence and the optimal position of induced learning intervals, with the objective of minimizing makespan.