Efficient algorithms for scheduling semiconductor burn-in operations
Operations Research
Scheduling to minimize average completion time: off-line and on-line approximation algorithms
Mathematics of Operations Research
Heuristics for hybrid flow shops with controllable processing times and assignable due dates
Computers and Operations Research
Approximation Schemes for Minimizing Average Weighted Completion Time with Release Dates
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Note: minimizing makespan with release times on identical parallel batching machines
Discrete Applied Mathematics
Scheduling two-stage hybrid flow shop with availability constraints
Computers and Operations Research
Batch processing with interval graph compatibilities between tasks
Discrete Applied Mathematics
Approximation schemes for constrained scheduling problems
SFCS '89 Proceedings of the 30th Annual Symposium on Foundations of Computer Science
Flowshop scheduling problem with a batching machine and task compatibilities
Computers and Operations Research
Minimizing makespan in hybrid flowshops
Operations Research Letters
Heuristic algorithms for the two-stage hybrid flowshop problem
Operations Research Letters
Scheduling an unbounded batching machine with job processing time compatibilities
Discrete Applied Mathematics
Journal of Intelligent Manufacturing
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This paper considers a two-stage hybrid flowshop problem in which the first stage contains several identical discrete machines, and the second stage contains several identical batching machines. Each discrete machine can process no more than one task at time, and each batching machine can process several tasks simultaneously in a batch with the additional feature that the tasks of the same batch have to be compatible. A compatibility relation is defined between each pair of tasks, so that an undirected compatibility graph is obtained which turns out to be an interval graph. The batch processing time is equal to the maximal processing time of the tasks in this batch, and all tasks of the same batch start and finish together. The goal is to make batching and sequencing decisions in order to minimize the makespan. Since the problem is NP-hard, we develop several heuristics along with their worst cases analysis. We also consider the case in which tasks have the same processing time on the first stage, for which a polynomial time approximation scheme (PTAS) algorithm is presented.