Multi-objective modelling of sustainable closed-loop supply chain network with price-sensitive demand and consumer’s incentives

• Developed multi-objective optimisation model for sustainable CLSC network problem. Considered SCs complexity, price-sensitive demand and consumer’s incentives. Data collected from a leading European household appliance company was used. Evidenced the positive effects of incentive pricing on returned goods. Provided multiple trade-off solutions decision makers. Closed-loop supply chains (CLSCs) are essential maximising value creation over entire life cycle product. The design these networks is increasing due to growing online businesses rising sustainability awareness. This study develops problem considering chain’s inherent complexity (multi-echelon, multi-product, multi-mode multi-period nature) along with demand, incentives different quality levels proposed seeks optimise total cost carbon emissions generated by production, distribution, transportation, disposal activities. A two-stage algorithm, through integration Non-Dominated Sorting Genetic Algorithm (NSGA-II) Co-Kriging approach utilised determine between costs in network. used analyse interpret developed model. results show that provides robust outcomes computationally less expensive than epsilon constraint approach. evidences goods reverse logistics chain managers make informed decisions.