A decision support framework for sustainable production planning of paper recycling systems
Paper waste is a growing concern, mainly because customers use various paper weights and sizes. To tackle this issue and meet customer demands, it is crucial to plan paper recycling systems efficiently. This study focuses on developing an efficient decision-making framework. We start with a mathematical model that addresses the cutting stock problem, considering two different production systems: make-to-stock and make-to-order. Our model generates practical production plans for a paper recycling system using data from Enterprise Resource Planning modules.
To make our framework sustainable, we incorporate two different methods: the fuzzy best-worst method and a double normalization-based multiple aggregation technique. These methods help us evaluate various criteria, such as human resource usage and energy consumption while considering environmental uncertainties. Additionally, we use a neural network-based multiple regression model to estimate sales for each production plan, providing an income-based evaluation criterion. The results of this study aim to present the most sustainable and efficient production plans. By minimizing waste and meeting customer demands, we contribute to a more environmentally friendly and customer-satisfying paper recycling process.
Yousefi, S., Baqeri, M., Tosarkani, B. M., Hassanzadeh Amin, S., & Zolfagharinia, H. (2023). A decision support framework for sustainable production planning of paper recycling systems (external link, opens in new window) . Computers & Industrial Engineering, Volume 183, 109500.
