An application area of this
research of particular interest to us is robust portfolio
selection. Another aspect of our research on conic programs is focused on
developing efficient branch-and-cut algorithms for solving mixed integer
conic programs. Mixed integer conic programs are natural models for a
wide
variety of optimization problems such as the max-cut, the traveling
salesman problem, robust eigenvalue problem, etc. Recently we have also
begun exploring barrier/penalty function methods for controlling
stochastic
networks.