Semi-deterministic and genetic algorithms for global optimization of microfluidic protein folding devices

Abstract

In this paper we reformulate global optimization problems in terms of boundary value problems (BVP). This allows us to introduce a new class of optimization algorithms. Indeed, current optimization methods, including non-deterministic ones, can be seen as discretizations of initial value problems for differential equations, or systems of differential equations. Furthermore, in order to reduce computational time approximate state and sensitivity evaluations are introduced during optimization. Lastly, we demonstrated the efficacy of two algorithms, included in the former class, on two academic test cases and on the design of a fast microfluidic protein folding device. The aim of the latter design is to reduce mixing times of proteins to microsecond timescales. Results are compared with those obtained with a classical genetic algorithm.