Name
Abstract | ||
|---|---|---|
We consider an online scheduling problem where jobs arrive over time. A set of independent jobs has to be scheduled on two parallel machines, where preemption is not allowed and the number of jobs is unknown in advance. The characteristics of each job, i.e., processing time and delivery time, become known at its release date. Each job is delivered to the destination independently and immediately at its completion time on the machines. The objective is to minimize the time by which all jobs have been delivered. We present an online algorithm which has a competitive ratio of $$(1+\\sqrt{5})/2\\approx 1.618$$(1+5)/2¿1.618. Finally, our experimental results show that, in practice, the worst case error ratio is much better than the theoretical bound. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-03780-6_9 | Journal of Combinatorial Optimization |
Keywords | Field | DocType |
Scheduling,Delivery times,Parallel machines,Online algorithm | Online algorithm,Worst case error,Mathematical optimization,Preemption,Job shop scheduling,Approx,Release date,Scheduling (computing),Computer science,Competitive analysis | Journal |
Volume | Issue | ISSN |
30 | 2 | 1382-6905 |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peihai Liu | 1 | 52 | 6.01 |
| Xiwen Lu | 2 | 182 | 21.03 |