Multi-objective optimization of adiabatic styrene reactors using Generalized Differential Evolution 3 (GDE3)

Abstract

In this study, industrial styrene reactors were optimized using the multi-objective algorithm Generalized Differential Evolution 3 (GDE3) to maximize their conversion and selectivity. When modeling the reactors, an intrinsic heterogeneous reaction model was adopted to produce realistic results, which would adequately encompass the complex influence of the decision variables in the system. Several optimal scenarios were obtained using two- and three-objective approaches, which can be used in integrated process analysis to define suitable operational conditions. These scenarios were studied from a fundamental perspective to explore the impact of the steam-to-ethylbenzene molar feed ratio, the number of catalyst beds, catalyst loading, operating pressure, and inlet temperatures on reactor performance. Furthermore, our GDE3 implementation has been made available in a public code repository and a Python package.