Stowage Planning to Minimize Travelling Energy Consumption of Terminal Vehicles

The increasing size and complexity of modern container ships necessitate more efficient and sustainable terminal operations. This study addresses the detailed stowage planning problem from the perspective of terminal planners, with a novel objective: minimizing the energy consumption of container handling vehicles operating between yard positions and quay-side loading bays. A Mixed Integer Linear Programming (MILP) model is proposed to optimize container-to-slot assignments, considering compatibility constraints, weight distribution, and predefined aggregate stowage plans. The objective function combines a lexicographic penalty scheme prioritizing plan adherence with a distance-based energy cost minimization. The model explicitly integrates operational constraints related to stack formation and stability while ensuring feasibility through soft constraints for deviations and unassigned containers. Computational experiments on a realistic dataset comprising 329 containers demonstrate the model’s effectiveness, achieving an optimal solution in under a few minutes with no unassigned containers and minimal deviation from the aggregated plan. Results confirm that the proposed approach enables energy-efficient container allocation without compromising operational constraints, offering a promising direction for green port operations.