A Multi-Objective Process Optimization Procedure under Uncertainty for Sustainable Process Design

Sustainable chemical process design can be formulated as a multi-objective optimization (MOO) problem covering economic, environmental and societal aspects. Moreover, uncertainties are unavoidable during the process design. So, uncertainties should be involved in the optimization. In this work, authors work on the basis of stochastic programming to deal with uncertainty factors, and integrate MOO deterministic algorithms to identify the optimal process design for the improvement of sustainability from a number of alternatives. The efficacy of the procedure is demonstrated by design of 1-hexene separation process.