Floating Automated Targeting for Resource Conservation Networks

Abstract

Over the past decades, many systematic process integration techniques have been developed for synthesizing resource conservation networks (RCNs). Automated Targeting Model (ATM) is one of the approaches that incorporates insight-based concept into mathematical optimization model to locate various targets for RCNs. However, in order to perform automated targeting, the quality values of process sinks and sources must be first identified and arranged in ascending or descending order. Therefore, for cases where the quality of process sinks and sources are given in a range and not fixed, the conventional ATM will not able to locate the targets accordingly. To overcome such limitation, a novel Floating Automated Targeting Model (FATM) is presented in this work. Two literature case studies are solved to illustrate the proposed approach.