AI-enhanced simulation for sustainable production in pulp and paper industry

Abstract

This study investigates how environmental policies influence production planning in environmentally sensitive manufacturing systems, particularly in the paper and pulp industry. Despite growing regulatory pressure and consumer awareness, existing research often overlooks the integration of environmental policies with operational uncertainty. To address this gap, we propose the Environmental Hedging Point Policy (EHPP) as a strategic framework that draws on optimal control theory to dynamically balance sustainability and operational performance under uncertainty. Our approach combines simulation-based optimization with multi-objective particle swarm optimization and K-means clustering to evaluate trade-offs between cost, customer satisfaction, and environmental impact. We model a dynamic demand environment shaped by eco-conscious customer preferences and test policy scenarios using data from a paper manufacturing system involving both recyclable and virgin paper inputs. The results provide actionable insights for policymakers and manufacturers, supporting sustainable production planning under uncertainty.