Minimizing the sum of the k largest functions in linear time
Information Processing Letters
Exact procedures for solving the discrete ordered median problem
Computers and Operations Research
A flexible model and efficient solution strategies for discrete location problems
Discrete Applied Mathematics
Aggregation in hub location problems
Computers and Operations Research
New results on minimax regret single facility ordered median location problems on networks
ESA'07 Proceedings of the 15th annual European conference on Algorithms
The gravity multiple server location problem
Computers and Operations Research
An aggregation heuristic for large scale p-median problem
Computers and Operations Research
Profit Maximizing Distributed Service System Design with Congestion and Elastic Demand
Transportation Science
On the ordered anti-Weber problem for any norm in R2
Operations Research Letters
The stochastic p-median problem with unknown cost probability distribution
Operations Research Letters
On the exponential cardinality of FDS for the ordered p-median problem
Operations Research Letters
Algorithmic results for ordered median problems
Operations Research Letters
| Hi-index | 0.01 |
Many location models involve distances and demand points in their objective function. In urban contexts, there can be millions of demand points. This leads to demand point aggregation, which produces error. We identify a general model structure that includes most such location models, and present a means of obtaining error bounds for all models with this structure. The error bounds suggest how to do the demand point aggregation so as to keep the error small.