Sustainable scheduling of batch processes under economic and environmental criteria with MINLP models and algorithms

• Sustainable scheduling for multiproduct and multipurpose batch plants is investigated.
• Multi-objective optimization model under economic and environmental criteria is proposed.
• Maximizing productivity as the economic objective.
• Minimizing environmental impact per functional unit as the environmental objective.
• Tailored Dinkelbach's algorithm and reformulation-linearization method to optimize resulting MILFP problems effectively.

We address the bi-criterion optimization of batch scheduling problems with economic and environmental concerns. The economic objective is expressed in terms of productivity, which is the profit rate with respect to the makespan. The environmental objective is evaluated by means of environmental impact per functional unit based on the life cycle assessment methodology. The bi-criterion optimization model is solved with the ε-constraint method. Each instance is formulated as a mixed-integer linear fractional program (MILFP), which is a special class of non-convex mixed-integer nonlinear programs. In order to globally optimize the resulting MILFPs effectively, we employ the tailored reformulation-linearization method and Dinkelbach's algorithm. The optimal solutions lead to a Pareto frontier that reveals the tradeoff between productivity and environmental impact per functional unit. To illustrate the application, we present two case studies on the short-term scheduling of multiproduct and multipurpose batch plants.