The objective of this work is to present a quantitative tool to support decision-making in the area of optimal design of supply chains (SC) for the combined production of sugar and ethanol. The problem is formulated as a multiobjective mixed-integer linear program that seeks to optimize simultaneously the economic and environmental performance of the production chain. The advantages of the approach presented are illustrated through its application to a case study, in which a trade-off exists between the economic and environmental performance of the network. Our method provides valuable insight into the problem and a guide to adopt more sustainable strategic alternatives in the design of SCs with embedded biorefineries.
This work presents a novel approach that addresses the management of chemical supply chains (SCs) under demand uncertainty. One of the main objectives is to overcome the numerical difficulties associated with solving the underlying large-scale mixed integer nonlinear problem (MINLP). The approach that is proposed relies on a simulation-based optimization strategy that uses a discrete-event system to model the SC. Within this framework, each SC entity is represented as an agent whose activity is described by a collection of states and transitions. The overall system is coupled with an optimization algorithm that is designed to improve its operation. This strategy is a very attractive alternative in the field of decision-making processes under uncertainty, the advantages of which are highlighted with some cases of SC networks that are composed of several plants, warehouses, distribution centers, and retailers.
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.