Multi-modal transport of perishable products with demand uncertainty and empty repositioning: A scenario-based rolling horizon framework

We study the planning of a multi-modal transportation system with perishable products, demand uncertainty and repositioning empty Returnable Transport Items (RTIs). propose rolling horizon framework where we periodically re-optimize. As such, relevant responses actions to new occurred are taken, possible updates plans can be made. Our considers customer demand, formulated as Scenario-based Two-Stage Program (STSP) for which set scenarios is generated. An Adaptive Large Neighborhood Search (ALNS) algorithm used solve this scenario-based problem. proposed ALNS employs operators strategies complex large give detailed computational analysis on properties our framework, evaluating effects stochastic provide practical insights.