The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
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...
Abstract. We consider the Steiner tree problem under a 2-stage stochastic model with recourse and finitely many scenarios (SSTP). Thereby, edges are purchased in the first stage wh...
In this paper we apply the well known sample average approximation (SAA) method to solve a class of stochastic variational inequality problems (SVIPs). We investigate the existenc...
Abstract-Joint subcarrier, power and rate allocation in orthogonal frequency division multiple access (OFDMA) scheduling is investigated for both downlink and uplink wireless trans...