Automated targeting model for aggregate planning in production and energy supply chains

Aggregate planning aims to maximize profit for a supply chain while satisfying its demand. In this work, the automated targeting model (ATM) that was originally developed for resource conservation network is extended for use in aggregate planning for production and energy supply chains. The ATM is an optimization framework that is based on the insight-based technique of pinch analysis, with the philosophy in setting target(s) ahead of detailed planning. Being an optimization framework, the ATM offers other advantages than conventional pinch analysis technique by incorporating more case-specific constraints, and is able to handle more complex optimization problems. Three literature examples and an industrial polymer production case study are solved to show the robustness of ATM.