Robust Polynomial-Time Approximation Schemes for Parallel Machine Scheduling with Job Arrivals and Departures
成果类型:
Article
署名作者:
Skutella, Martin; Verschae, Jose
署名单位:
Technical University of Berlin; Pontificia Universidad Catolica de Chile
刊物名称:
MATHEMATICS OF OPERATIONS RESEARCH
ISSN/ISSBN:
0364-765X
DOI:
10.1287/moor.2015.0765
发表日期:
2016
页码:
991-1021
关键词:
improved bounds
online
algorithms
packing
摘要:
Scheduling a set of n jobs on m identical parallel machines so as to minimize the makespan or maximize the minimum machine load are two of the most important and fundamental scheduling problems studied in the literature. We consider the general online scenario where jobs are consecutively added to and/or deleted from an instance. The goal is to maintain a near-optimal assignment of the current set of jobs to the m machines. This goal is essentially doomed to failure unless, upon arrival or departure of a job, we allow reassigning some other jobs. Considering that the reassignment of a job induces a cost proportional to its size, the total cost for reassigning jobs must preferably be bounded by a constant r times the total size of added or deleted jobs. The value r is called the reassignment factor of the solution and it is a measure of our willingness to adapt the solution over time. Our main result is that, for any epsilon > 0, it is possible to achieve (1 + epsilon)-competitive solutions with constant reassignment factor r(epsilon). For the minimum makespan problem this is the first improvement on the (2 + epsilon)-competitive algorithm by Andrews et al. (1999) [Andrews M, Goemans M, Zhang L (1999) Improved bounds for on-line load balancing. Algorithmica 23(4):278-301]. Crucial to our algorithm is a new insight into the structure of robust, almost optimal schedules.