A decision support framework for sustainable production planning of paper recycling systems

The paper waste generation is exacerbated due to the wide variety of weights and sizes specified by customers. Hence, sustainable production planning of paper recycling systems has become critical to reduce potential waste while addressing customers' demands. This study aims to develop a decision-support framework starting with a mathematical programming model to address the cutting stock problem focusing on make-to-stock and make-toorder production systems simultaneously. The proposed model generates various feasible production plans for a paper recycling system considering practical assumptions and recorded operational data from the Enterprise Resource Planning modules. The developed framework also integrates the fuzzy best-worst method and double normalization-based multiple aggregation technique to consider sustainability-related evaluation criteria (e.g., human resource usage and energy consumption) to prioritize the obtained production plans in an uncertain environment. Furthermore, a neural network-based multiple regression model is utilized to estimate the sales amount for each production plan to calculate the income as an evaluation criterion. The outputs of this study introduce the most sustainable and efficient production plans to minimize waste and satisfy customers' demands.