Sequential sampling for solving stochastic programs

We develop a sequential sampling procedure for solving a class of stochastic programs. A sequence of feasible solutions, with at least one optimal limit point, is given as input to our procedure. Our procedure estimates the optimality gap of a candidate solution from this sequence, and if that point estimate is sufficiently small then we stop. Otherwise, we repeat with the next candidate solution from the sequence with a larger sample size. We provide conditions under which this procedure: (i) terminates with probability one and (ii) terminates with a solution which has a small optimality gap with a prespecified probability.

• Type: Conference
• Year: 2007
• Where: WSC
• Authors: Güzin Bayraksan, David P. Morton
• Keywords: Candidate Solution, Modeling And Simulation, Optimality Gap, Sequential Sampling Procedure, WSC 2007