The goal of group technology in manufacturing process is to identify a set of products with similar processing requirements and minimize machine changeover and setup. Although different models of joint deterioration and learning effects have been extensively studied in various areas, it has rarely been studied in the context of group scheduling. In this article, we consider single-machine scheduling problems involving deterioration and learning effects simultaneously under the group technology and the group availability assumptions. We assume that the group setup time is a function of position-dependent learning while the actual processing time of a job is a function of joint time-dependent deterioration and position-dependent learning. We further assume that after the setup, the machine deterioration will reset first and then starts anew. We prove that the makespan and the total completion time minimization problems can be optimally solved in polynomial time algorithms with agreeable conditions.