  In this paper, we introduce an Augmented Lagrangian based method to
incorporate the multiple objectives (MO) in a search ranking algorithm.
Optimizing MOs is an essential and realistic requirement for building ranking
models in production. The proposed method formulates MO in constrained
optimization and solves the problem in the popular Boosting framework -- a
novel contribution of our work. Furthermore, we propose a procedure to set up
all optimization parameters in the problem. The experimental results show that
the method successfully achieves MO criteria much more efficiently than
existing methods.
