A Resilience Analysis Approach for Process Design, Integration and Optimization

Abstract

Resilience in response to disruption events is critical to the economic performance of process systems, but this concept has received limited attention in the literature. A general framework for resilience optimization is proposed to incorporate an improved quantitative measure of resilience and a comprehensive set of resilience enhancement strategies for process design and operations. The proposed framework identifies a set of disruptive events for a given system, and then formulates a multiobjective two-stage adaptive robust mixed-integer fractional programming model to optimize the resilience and economic objectives simultaneously. The model accounts for network configuration, equipment capacities, and capital costs in the first stage, and the number of available processes and operating levels in each time period in the second stage. The applicability of the proposed framework is demonstrated through an application on process network design and planning.