Deteriorating and position-based learning effects on some single-machine scheduling problems

Integrates learning effects with different position-dependent learning impact factors and deteriorating effects, a general model is developed in this paper. We prove that the single-machine scheduling problems with the developed model are optimally solvable in polynomial time for optimizing makespan, total completion time and the sum of (square) completion times. Those to minimize the total weighted completion time and the maximum lateness are proved to be optimally solvable in polynomial time only for certain assumptions. Optimal solutions are demonstrated by an example for the considered problems using the constructed optimal rules.