Single-Machine Group Scheduling Model with Position-Dependent and Job-Dependent DeJong’s Learning Effect

Abstract

This paper considers the single-group scheduling models with Pegels’ and DeJong’s learning effect and the single-group scheduling models with Pegels’ and DeJong’s aging effect. In a classical scheduling model, Pegels’ and DeJong’s learning effect is a constant or position-dependent, while the learning effect and aging effect are job-dependent in this paper. Compared with the classical learning model and aging model for scheduling, the proposed models are more general and realistic. The objective functions are to minimize the total completion time and makespan. We propose polynomial time methods to solve all the studied problems.