On the performance of on-line algorithms for partition problems
Acta Cybernetica
An on-line scheduling heuristic with better worst case ratio than Graham's list scheduling
SIAM Journal on Computing
New algorithms for an ancient scheduling problem
Journal of Computer and System Sciences - Special issue on selected papers presented at the 24th annual ACM symposium on the theory of computing (STOC '92)
A better algorithm for an ancient scheduling problem
Journal of Algorithms
On-line routing of virtual circuits with applications to load balancing and machine scheduling
Journal of the ACM (JACM)
Better Bounds for Online Scheduling
SIAM Journal on Computing
Generating adversaries for request-answer games
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Multiprocessor Scheduling with Rejection
SIAM Journal on Discrete Mathematics
On-line load balancing for related machines
Journal of Algorithms
Preemptive multiprocessor scheduling with rejection
Theoretical Computer Science
Developments from a June 1996 seminar on Online algorithms: the state of the art
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Online scheduling on two uniform machines to minimize the makespan
Theoretical Computer Science
Note: Tight bounds for bandwidth allocation on two links
Discrete Applied Mathematics
Online scheduling with reassignment on two uniform machines
Theoretical Computer Science
Online scheduling with rearrangement on two related machines
Theoretical Computer Science
Optimal semi-online algorithms for scheduling problems with reassignment on two identical machines
Information Processing Letters
Online scheduling with reassignment
Operations Research Letters
New lower and upper bounds for on-line scheduling
Operations Research Letters
| Hi-index | 5.23 |
We study an online scheduling problem with rejection, in which some rearrangement of the solution is allowed. This problem is called scheduling with rejection and withdrawal. Each arriving job has a processing time and a rejection cost associated with it, and it needs to be either assigned to a machine or rejected upon arrival. At termination, it is possible to choose at most a fixed number of scheduled jobs and withdraw them (i.e., decide to reject them). We study the minimization version, where the goal is to minimize the sum of the makespan and the total rejection cost (which corresponds to the penalty), and the maximization problem, where the goal is to maximize the sum of the minimum load and the total rejection cost (which corresponds to profit). We study environments of machines, which are the case of m identical machines and the case of two uniformly related machines, and show a strong relation between these problems and the related classic online scheduling problems which they generalize, in contrast to standard scheduling with rejection, which typically makes the scheduling problems harder.