| Article ID: | iaor2012543 |
| Volume: | 63 |
| Issue: | 3 |
| Start Page Number: | 293 |
| End Page Number: | 298 |
| Publication Date: | Mar 2012 |
| Journal: | Journal of the Operational Research Society |
| Authors: | Ng C T, Zhang L Q, Lu L F |
| Keywords: | markov processes |
In this paper, we consider the unbounded parallel‐batch scheduling with rejection. A job is either rejected, in which case a certain penalty has to be paid, or accepted and processed in batches on a machine. The processing time of a batch is defined as the longest processing time of the jobs contained in it. Four problems are considered: (1) to minimize the sum of the total completion time of the accepted jobs and the total rejection penalty of the rejected jobs; (2) to minimize the total completion time of the accepted jobs subject to an upper bound on the total rejection penalty of the rejected jobs; (3) to minimize the total rejection penalty of the rejected jobs subject to an upper bound on the total completion time of the accepted jobs; (4) to find the set of all the Pareto optimal schedules. We provide a polynomial‐time algorithm for the first problem. Furthermore, we show that all the other three problems are binary NP‐hard and present a pseudo‐polynomial‐time algorithm and a fully polynomial‐time approximation scheme for them.