Stochastic branch bound applying target oriented branch bound method to optimal scenario tree reduction

摘要

In this article a new branch & bound method is described. It uses an artificial target to improve its bounding capabilities. Therefore the new approach is faster compared to the classical one. It is applied to the stochastic problem of optimal scenario tree reduction. The aspects of global optimization are emphasized here. All necessary components for that problem are developed and some experimental results underline the benefits of the new approach. (author's abstract)