On precision of optimization in the case of incomplete information

<p><span style="font-size: 11.000000pt; font-family: 'CMR10';">In the paper we study the impact of incomplete information to precision of results of stochastic optimization. It is assumed that the stochastic characteristics of optimized system are evaluated from the data. However, the observations can be incom- plete, namely, we consider the random censoring frequently encountered in time-to-event or lifetime studies. The analysis of uncertainty of solution is based both on theoretical properties of estimated stochastic characteristics and on simulated examples. </span>