Multi-stage distributionally robust optimization with risk aversion

By Ripeng Huang, Shaojian Qu, Xiaoguang Yang, Zhimin Liu. Journal of Industrial and Management Optimization, 2021

49 citations recorded by the source corpus.

Two-stage risk-neutral stochastic optimization problem has been widely studied recently. The goals of our research are to construct a two-stage distributionally robust optimization model with risk aversion and to extend it to multi-stage case. We use a coherent risk measure, Conditional Value-at-Risk, to describe risk. Due to the computational complexity of the nonlinear objective function of the proposed model, two decomposition methods based on cutting planes algorithm are proposed to solve the two-stage and multi-stage distributional robust optimization problems, respectively. To verify the validity of the two models, we give two applications on multi-product assembly problem and portfolio selection problem, respectively. Compared with the risk-neutral stochastic optimization models, the proposed models are more robust.

Subfields: Control and Systems Engineering, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/c49d70d0c6f74d0438e2ee5b570515556a4ea2c0