An integrated local search method for inventory and routing decisions
Expert Systems with Applications: An International Journal
Invited Review: Industrial aspects and literature survey: Combined inventory management and routing
Computers and Operations Research
A branch-and-price algorithm for an integrated production and inventory routing problem
Computers and Operations Research
Analysis of the maximum level policy in a production-distribution system
Computers and Operations Research
The biobjective inventory routing problem: problem solution and decision support
INOC'11 Proceedings of the 5th international conference on Network optimization
The inventory-routing problem with transshipment
Computers and Operations Research
A Column-Generation Based Tactical Planning Method for Inventory Routing
Operations Research
Robust Inventory Routing Under Demand Uncertainty
Transportation Science
The exact solution of several classes of inventory-routing problems
Computers and Operations Research
Evolutionary approach in inventory routing problem
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
Survey of Green Vehicle Routing Problem: Past and future trends
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
We consider a distribution problem in which a product has to be shipped from a supplier to several retailers over a given time horizon. Each retailer defines a maximum inventory level. The supplier monitors the inventory of each retailer and determines its replenishment policy, guaranteeing that no stockout occurs at the retailer (vendor-managed inventory policy). Every time a retailer is visited, the quantity delivered by the supplier is such that the maximum inventory level is reached (deterministic order-up-to level policy). Shipments from the supplier to the retailers are performed by a vehicle of given capacity. The problem is to determine for each discrete time instant the quantity to ship to each retailer and the vehicle route. We present a mixed-integer linear programming model and derive new additional valid inequalities used to strengthen the linear relaxation of the model. We implement a branch-and-cut algorithm to solve the model optimally. We then compare the optimal solution of the problem with the optimal solution of two problems obtained by relaxing in different ways the deterministic order-up-to level policy. Computational results are presented on a set of randomly generated problem instances.