An integrated optimization framework for reverse supply chain design in plastic waste management

This paper develops a mixed-integer linear programming (MILP) model to optimize a municipal reverse-logistics systems for plastic waste recovery. Two scenarios are examined: a baseline configuration and an enhanced configuration that integrates community-level collection efforts and government incentives. A prescriptive analytics results show that the enhanced scenario achieves a substantial reduction in total environmental cost—from IDR 1.813 billion to IDR 0.182 billion—equivalent to a 90% improvement in environmental dimension. The intervention also increases system performance by nearly halving uncollected plastic waste (from 35,780 to 18,176 Kg) and reducing unmet market demand. A significant shift in the cost structure is observed, with inefficient downstream cost components declining sharply. In contrast, market- and processing-related components become more prominent, indicating a transition toward a more circular, market-oriented waste-management system. Despite these improvements, residual uncollected waste and unmet demand highlight remaining operational constraints. The network optimization underscores the role of integrated public participation and targeted subsidies as effective levers for achieving cost-efficient, environmentally aligned Polyethylene Terephthalate (PET) waste management, while recommending further investments in processing capacity and in supply–demand coordination.