Name
Title | ||
|---|---|---|
A versatile adaptive aggregation framework for spatially large discrete location-allocation problems. |
Abstract | ||
|---|---|---|
•An adaptive aggregation framework for discrete location-allocation problems is proposed.•The mechanism relies on the adjustment of data aggregation to high quality solutions.•Adaptive aggregation is more beneficial than the elimination of aggregation errors.•Adaptive aggregation framework significantly enhances capabilities of conventional methods. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.cie.2017.07.022 | Computers & Industrial Engineering |
Keywords | Field | DocType |
Data aggregation,Location analysis,Adaptive aggregation,Framework,Heuristics | Mathematical optimization,Minimax,Location-allocation,Computational mathematics,Facility location problem,Heuristics,Computer memory,Data aggregator,Mathematics,Operations management,Computation | Journal |
Volume | ISSN | Citations |
111 | 0360-8352 | 2 |
PageRank | References | Authors |
0.39 | 23 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matej Cebecauer | 1 | 3 | 0.74 |
| Lubos Buzna | 2 | 196 | 27.21 |