An important attribute of a supply chain in a competitive and volatile market environment is the ability to respond rapidly to demand variation. A particularly relevant application is the forest products industry, where a promising strategy to improve the struggling business model entails the shift from commodity products toward high-value specialty products. A key implication is that new process and supply chain designs have sufficient capability to respond quickly to market changes, such that product availability is high. In this study, we develop a computational framework for dynamic operability analysis of process supply chains. A dynamic model of a multiproduct, multiechelon system supply chain system is developed, and incorporated within an optimization framework. A two-stage stochastic programming approach is applied for the treatment of demand uncertainty. A bicriterion optimization problem is formulated for generating the Pareto frontier between an economic and responsiveness criterion. Two case studies are presented to demonstrate the applicability of this framework.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.