Computers & Chemical Engineering, Vol.111, 92-101, 2018
Bounded-error optimal experimental design via global solution of constrained min-max program
We present an improvement of existing methods for globally solving optimal experimental design (OED) for bounded-error estimation based on a bilevel formulation from Mukkala et al. (2017). The proposed solution method for the min-max program is based on our method for generalized semi-infinite programs (via restriction of the right-hand side). The algorithm employed has the advantage that it guarantees a global solution for the OED assuming the global solution of two subproblems. To obtain a feasible solution only the lower-level problem has to be solved globally. In case of a local solution of the upper-level problem, the solution is still feasible though it is an upper bound of the global solution. The min-max method for OED is illustrated with four examples: two simple chemical reactions, BET-adsorption and a reformulated predator-prey system. The benefits of global methods are shown along with the limitations of state-of-the-art global solvers. (C) 2018 Elsevier Ltd. All rights reserved.
Keywords:Optimal experimental design;Bounded-error estimation;Set-membership estimation;Global optimization;Min-max problems