Demo Data from VLDB 2026 / reviewers in the wild / expert
Jack S. Cook
dblp:28/6573
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1994
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Mathematical optimization › integer programming › binary optimization
0-1 integer programming |
0.0 | 1 | 1994 | Optimal robot selection and workstation assignment for a CIM system · IEEE Trans. Robotics Autom. 1994 |
Methods — techniques the papers use, named apart from their topics
three-phase optimization algorithm · 0.00-1 mathematical programming · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1994 | Optimal robot selection and workstation assignment for a CIM systemabstractIn this paper, a mathematical program and solution algorithm is developed for optimal robot selection and workstation assignment for a CIM system. In specific, our model considers selection of a proper mix of multiple-type robots such that operational requirements from a given number of work- stations are satisfied at minimal system cost. Each robot is characterized by its fixed charge, and subject to limits on machine time and work envelope. Each workstation has known demands on both robot machine time and work space. The model is formulated as a pure 0-1 mathematical program and is shown harder than two-dimensional bin packing, a well-known NP-hard problem. A three-phase optimization algorithm is implemented and tested by solving 450 randomly generated problems. Computational results indicate the solution algorithm is effective in solving problems of a practical size (i.e., 50 workstations and a maximum of 20 robots) within acceptable computational times.> Jack S. Cook, Bernard T. Han |
IEEE Trans. Robotics Autom. | 1 |