A Permutation-Based Neighborhood for the Blocking Job-Shop Problem with Total Tardiness Minimization
The consideration of blocking constraints refers to the absence of buffers in a production system. A job-shop scheduling problem with a total tardiness objective is NP-hard even without blocking constraints and mathematical programming results indicate the necessity of heuristics. The neighborhood is one of its main components. In contrast to classical job-shop scheduling, a permutation of operations does not necessarily define a feasible schedule. A neighbor is determined by an adjacent pairwise interchange (API) of two operations on a machine and the resulting permutation of operations is modified to regain feasibility while maintaining the given API. The neighborhood is implemented in a simulated annealing and tested on train-scheduling-inspired problems as well as benchmark instances. The heuristic method obtains optimal and near-optimal solutions for small instances and outperforms a given MIP formulation for some of the larger ones.
KeywordsJob-shop scheduling Blocking Simulated annealing
- 4.Lange, J., & Werner, F. (2017). Approaches to modeling train scheduling problems as job-shop problems with blocking constraints. Journal of Scheduling. https://doi.org/10.1007/s10951-017-0526-0.
- 7.Oddi, A., Rasconi, R., Cesta, A., & Smith, S. F. (2012). Iterative improvement algorithms for the blocking job shop. In ICAPS.Google Scholar
- 8.Pranzo, M., & Pacciarelli, D. (2013). An iterated greedy metaheuristic for the blocking job shop scheduling problem. Journal of Heuristics, 1–25.Google Scholar
- 9.Lawrence, S. (1984). Supplement to resource constrained project scheduling: an experimental investigation of heuristic scheduling techniques. Pittsburgh: GSIA, Carnegie Mellon University.Google Scholar