: This paper presents a demand-based engineering method for designing radio networks of cellularmobile communicationsystems. The proposed procedure is based on a forward-engineerin...
Robust optimization has traditionally focused on uncertainty in data and costs in optimization problems to formulate models whose solutions will be optimal in the worstcase among ...
Kedar Dhamdhere, Vineet Goyal, R. Ravi, Mohit Sing...
The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
Borodin, Nielsen and Rackoff [5] proposed a framework for ing the main properties of greedy-like algorithms with emphasis on scheduling problems, and Davis and Impagliazzo [6] ext...
Some of the currently best-known approximation algorithms for network design are based on random sampling. One of the key steps of such algorithms is connecting a set of source nod...