Designing reverse logistics networks in shipyards: integrating cost, safety, and environmental trade-offs in location-routing decisions

The construction of large cruise ships generates complex reverse logistics flows due to design changes, delayed installations, and material excess, often resulting in site congestion, production inefficiencies, and safety hazards. This study develops a multi-level, multi-product, and multi-objective optimization model that integrates reverse logistics processes-returns, recycling, reuse, remanufacturing, and waste disposal-while explicitly incorporating health, safety, and environmental (HSE) objectives. To address the inherent complexity, fuzzy service time windows are introduced to quantify worker exposure risks alongside efficiency trade-offs. An Improved Discrete Crow Search Algorithm (IDCSA) is proposed, combining a multi-stage discrete encoding scheme with an ε-constraint method to enhance solution quality and diversity. Case studies of two shipyard scenarios demonstrate consistent trade-off patterns across different scales. Results indicate that minimizing costs often increases HSE risks, while achieving sustainability goals requires strategic investment. By integrating health, safety and environmental dimensions including health exposure, accident risk coefficients and environmental emissions into a unified reverse logistics location routing model, this study offers a distinctive contribution to sustainable shipyard logistics. Comparative results against the cost-time model demonstrate that the HSE integrated model proposed achieves an average reduction of approximately 7.15% in safety risks and 0.78% in health exposures, with only a marginal cost increase of around 1.44%. Sensitivity analysis reveals stable location and routing decisions in over 80% of scenarios, confirming the model’s robustness. The proposed framework supports decision-makers in aligning shipyard reverse logistics operations with sustainability and operational performance targets, offering practical insights for high-risk, large-scale maritime manufacturing environments.