VLDB 2026 Research / reviewers in the wild / expert
Marinella Giordano
dblp:83/2184
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2002
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Theoretical computer science
1 paper |
Mathematical optimization · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Performance modeling and evaluation · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Mathematical optimization
manufacturing system optimization |
0.0 | 1 | 2002 | Optimal Safety Stock for Unreliable, Finite Buffer, Single Machine Manufacturing Systems · ICRA 2002 |
Mathematical optimization › control theory
production system control |
0.0 | 1 | 2002 | Optimal Safety Stock for Unreliable, Finite Buffer, Single Machine Manufacturing Systems · ICRA 2002 |
Performance modeling and evaluation
queueing models |
0.0 | 1 | 2002 | Optimal Safety Stock for Unreliable, Finite Buffer, Single Machine Manufacturing Systems · ICRA 2002 |
Methods — techniques the papers use, named apart from their topics
numerical solution · 0.1fluid model · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | Optimal Safety Stock for Unreliable, Finite Buffer, Single Machine Manufacturing SystemsabstractA finite buffer, single part-type, single unreliable machine production system is considered. The part flow into the system is described through a fluid model. The problem is to determine a production control which minimizes an infinite horizon average back-log/surplus cost. In the infinite buffer capacity case, this problem is solved by a hedging point policy, and the hedging point can be analytically computed. In this paper we consider the finite capacity case, derive an equation to compute the optimal hedging point and solve it numerically. A comparison between the optimal hedging point in the finite buffer capacity case and the optimal hedging point in the infinite buffer capacity case is reported in the paper, together with the analysis of the effect of some meaningful parameters (like the buffer capacity and the demand loss cost) on the computed hedging point. Some numerical examples illustrate the results presented in the paper. Marinella Giordano, Francesco Martinelli |
ICRA | 1 |