Figure 3.

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.

MirĂ³ et al. BMC Bioinformatics 2012 13:90   doi:10.1186/1471-2105-13-90
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