Abstract
AbstractRescheduling can help to improve the quality of a schedule with respect to an initially given sequence. In this paper, we consider the possibility of rescheduling jobs arriving for processing at a single machine under the following limitations: (a) jobs can only be moved toward the end of the schedule and not toward the front, and (b) when a job is taken out of the sequence, it is put on a buffer of limited capacity before being reinserted in its new position closer to the end of the sequence. The buffer is organized as a stack with a last-in/first-out policy. As an objective function, we consider the minimization of the weighted number of late jobs. For this NP-hard problem, we first provide two different integer linear programming (ILP) formulations. Furthermore, we develop a branch-and-bound algorithm with a branching rule based on the movement of jobs. Then a new pseudo-polynomial dynamic programming algorithm is presented which utilizes dominance criteria and an efficient handling of states. Our computational experiments with up to 100 jobs show that this algorithm performs remarkably well and can be seen as the current method of choice.
Funder
Regione Lombardia
Karl-Franzens-Universität Graz
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Management Science and Operations Research,General Engineering,Software
Reference24 articles.
1. Abumaizar, R., & Svestka, J. (1997). Rescheduling job shops under random disruptions. International Journal of Production Research, 35(7), 2065–2082.
2. Agnetis, A., Hall, N. G., & Pacciarelli, D. (2006). Supply chain scheduling: Sequence coordination. Discrete Applied Mathematics, 154(15), 2044–2063.
3. Alfieri, A., Nicosia, G., Pacifici, & Pferschy, U. (2018a). Single machine scheduling with bounded job rearrangements. In: Proceedings of 16th cologne-Twente workshop on graphs and combinatorial optimization, 124–127.
4. Alfieri, A., Nicosia, G., Pacifici, A., & Pferschy, U. (2018b). Constrained Job Rearrangements on a Single Machine. In P. Daniele & L. Scrimali (Eds.), New Trends in Emerging Complex Real Life Problems, AIRO Springer Series (Vol. 1, pp. 33–41). Springer.
5. Ballestín, F., Pérez, A., & Quintanilla, S. (2019). Scheduling and rescheduling elective patients in operating rooms to minimise the percentage of tardy patients. Journal of Scheduling, 22(1), 107–118.