Optimization algorithm based on outer approximation. Our approach decomposes the problem into two subproblems: a master MILP, constructed by relaxing the original model using piecewise McCormick envelopes and hyper-planes, that provides a lower bound, and a slave NLP that yields an upper bound. The algorithm iterates between these two levels until a termination criterion is satisfied.
Miró et al. BMC Bioinformatics 2012 13:90 doi:10.1186/1471-2105-13-90