Integrating stochastic programming and reliability in the optimal synthesis of chemical processes

•Novel two-stage stochastic programming GDP (Generalized Disjunctive Programming) model with reliability constraints to deal with both the exogenous and endogenous uncertainties in process synthesis.•The reliability model is incorporated into the flowsheet superstructure optimization, considering the impact of selecting parallel units for improving plant availability.•Improved LOA algorithm to solve the hybrid GDP model with implicit nested disjunctions, obtaining optimal solutions by avoiding zero-flow numerical difficulties.•Quantification of the value of stochastic solution (VSS) and value of reliable solution (VRS) are used as the key measures for assessing the benefits of stochastic programming and reliability-based design optimization.•Simultaneous optimization of reliability and exogenous uncertainty in process design provides potential improvement for operational flexibility and economic performance.