A clustering approach for scenario tree reduction: an application to a stochastic programming portfolio optimization problem

作者：Beraldi Patrizia^*; Bruni Maria Elena

来源：Top, 2014, 22(3): 934-949.

DOI：10.1007/s11750-013-0305-9

• Scenario tree reduction
• Clustering algorithms
• Stochastic programming
• Portfolio optimization

This paper deals with the problem of scenario tree reduction for stochastic programming problems. In particular, a reduction method based on cluster analysis is proposed and tested on a portfolio optimization problem. Extensive computational experiments were carried out to evaluate the performance of the proposed approach, both in terms of computational efficiency and efficacy. The analysis of the results shows that the clustering approach exhibits good performance also when compared with other reduction approaches.

• 出版日期2014-10