A Scenario-Based Robust Optimization Model for Warehouse Planning in Shipbuilding Supply Chains under Ripple Effects

ანოტაცია

Shipbuilding supply chains (SSCs) are characterized by long production horizons and strong interdependencies among material flows. Disruptions affecting critical inputs such as steel plates, profiles, and pipes can rapidly propagate across multiple shipyards and parallel projects, generating ripple-effect-driven instability. Despite the relevance of this phenomenon, quantitative modeling efforts addressing ripple effects in shipbuilding logistics remain limited. This study develops a scenario-based robust optimization framework to support resilient material planning in shipbuilding supply chains under demand uncertainty. The supply network is modeled as a two-echelon structure in which material flows move from suppliers to candidate warehouses and subsequently to shipyards. Demand uncertainty is represented through discrete disruption scenarios reflecting increased material requirements. The proposed formulation focuses on evaluating system performance under adverse conditions by incorporating cost components associated with warehouse activation, material transportation, and unmet demand. The study presents an interpretable robust baseline model that evaluates warehouse activation and material flow decisions under progressively increasing disruption severity and also provides a structural basis for future stochastic extensions. Numerical results indicate that stable network configurations can be maintained as disruption severity increases, while system costs adjust in response to amplified material needs. Overall, the proposed framework provides an initial decision-support basis for analyzing warehouse configuration and material flow planning under ripple-effect conditions in shipbuilding supply chains. The findings show that a stable warehouse configuration can support resilient material planning, while operational flow adjustments absorb increasing demand pressure under ripple-effect conditions.