Study on Scheduling Problems with Learning Effects and Past Sequence Delivery Times

Abstract

In this paper, we study a single-machine green scheduling problem with learning effects and past-sequence-dependent delivery times. The problem can be properly applied to tackle green manufacturing where production and delivery time are variable and highly subject to process-reengineering. Our goal is to determine the optimal sequence such that total weighted completion time and maximum tardiness are minimized. For the general case, we provide the analysis procedure of lower bound, and also propose the heuristic and branch-and-bound algorithms. Furthermore, computational experiments are conducted to demonstrate the effectiveness of our algorithms.

Two Combinatorial Algorithms for the Constrained Assignment Problem with Bounds and Penalties

“…Second, it would be interesting to investigate the online version of this model, or its offline versions, with other objectives. Third, it would be interesting to study a more general setting of processing time, i.e., our model with learning effects or deterioration effects [30][31][32]. Finally, it would also be an interesting direction to consider our problem with release dates and submodular rejection penalties [33], which is defined as follows.…”