Abstract
The transition towards Circular Supply Chains (CSCs) represents a critical paradigm shift in the supply chain design context for enhancing sustainability across industrial ecosystems. However, existing network design models often lack a holistic integration of multi-dimensional sustainability objectives with dynamic operational features. This study thus addresses this gap by proposing a multi-objective, dynamic, multi-product model for the CSC network design, based on the Triple Bottom Line: economic, environmental, and social criteria. The model uniquely incorporates inter-organizational collaboration through external recovery and manufacturing, evaluates the viability of hybrid distribution-collection facilities, and treats facility capacity as a selectable decision variable rather than a binary choice. To tackle the problem’s complexity, a novel two-stage hybrid Non-dominated Sorting Genetic Algorithm II (NSGA-II) is developed. The algorithm decomposes the problem into a strategic facility location/allocation decision and a tactical material conveyance decision, embedded as a transshipment problem within the NSGA-II. The proposed algorithm is validated using exact ɛ-constraint solutions, demonstrating superior scalability for large-scale problem instances. Numerical results reveal a near-linear conflict between economic and environmental objectives, whereas the relationship between economic and social objectives exhibits a concave trade-off. Furthermore, sensitivity analysis indicates that while increasing product return rates enhances environmental outcomes, it may compromise economic and social viability due to reduced manufacturing requirements and elevated reverse logistics costs.