TB11 - Logistique / Logistics

We propose a two-stage stochastic mixed-integer programming model for a multi-compartment fuel distribution problem under demand uncertainty. The formulation emphasizes stability constraints governing load balance across compartments, while integrating routing and delivery decisions with multi-product flows and compartmentalized vehicle capacities. Two-stage stochastic programming - Multi-compartment vehicle routing - Load stability constraints

Picking is fundamental in warehouse logistics. Industry-motivated, we assume that precomputed 3D-bin packing solutions establish SKU picking orders for each picker. Considering scattered storage with limited stock, we optimize the total length of picker routes. We propose a branch-and-cut algorithm with cutting strategies, demonstrating effectiveness on generated and real-world instances.

We propose a destruction-reconstruction metaheuristic for multi-period electric vehicle charging station location and sizing to maximize covered demand. To accelerate the algorithm, we filter candidate solutions using a fast proxy objective. We test the algorithm across multiple allocation policies using realistic instances derived from Italian demographic data.
key words: EV charger location, Metaheuristic

We study the aircraft maintenance location-routing problem in airline operational planning that jointly optimizes maintenance facility location and aircraft routing decisions. To address this problem, we first propose a connection-based mixed-integer linear programming formulation and introduce several valid inequalities to strengthen it. Furthermore, we propose a branch-and-price approach to deal with large-scale instances. Finally, the performance of the proposed model and solution approach is evaluated through numerical experimental studies based on real operational data from an airline.