The vehicle routing problem
Combinatorial Algorithms
Deliveries in an Inventory/Routing Problem Using Stochastic Dynamic Programming
Transportation Science
Coordinating Production and Delivery Under a (z, Z)-Type Vendor-Managed Inventory Contract
Manufacturing & Service Operations Management
Deterministic Order-Up-To Level Policies in an Inventory Routing Problem
Transportation Science
The Stochastic Inventory Routing Problem with Direct Deliveries
Transportation Science
Supply chain scheduling: Batching and delivery
Operations Research
Dynamic Programming Approximations for a Stochastic Inventory Routing Problem
Transportation Science
A Decomposition Approach for the Inventory-Routing Problem
Transportation Science
The benefit of VMI strategies in a stochastic multi-product serial two echelon system
Computers and Operations Research
Enhancing supply chain decisions using constraint programming: a case study
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Expert Systems with Applications: An International Journal
Tabu search with path relinking for an integrated production-distribution problem
Computers and Operations Research
Analysis of the maximum level policy in a production-distribution system
Computers and Operations Research
A single supplier-single retailer system with an order-up-to level inventory policy
Operations Research Letters
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In this paper we consider a complex production-distribution system, where a facility produces (or orders from an external supplier) several items which are distributed to a set of retailers by a fleet of vehicles. We consider Vendor-Managed Inventory (VMI) policies, in which the facility knows the inventory levels of the retailers and takes care of their replenishment policies. The production (or ordering) policy, the retailers replenishment policies and the transportation policy have to be determined so as to minimize the total system cost. The cost includes the fixed and variable production costs at the facility, the inventory costs at the facility and at the retailers and the transportation costs, that is the fixed costs of the vehicles and the traveling costs. We study two different types of VMI policies: The order-up-to level policy, in which the order-up-to level quantity is shipped to each retailer whenever served (i.e. the quantity delivered to each retailer is such that the maximum level of the inventory at the retailer is reached) and the fill-fill-dump policy, in which the order-up-to level quantity is shipped to all but the last retailer on each delivery route, while the quantity delivered to the last retailer is the minimum between the order-up-to level quantity and the residual transportation capacity of the vehicle. We propose two different decompositions of the problem and optimal or heuristic procedures for the solution of the subproblems. We show that, for reasonable initial values of the variables, the order in which the subproblems are solved does not influence the final solution. We will first solve the distribution subproblem and then the production subproblem. The computational results show that the fill-fill-dump policy reduces the average cost with respect to the order-up-to level policy and that one of the decompositions is more effective. Moreover, we compare the VMI policies with the more traditional Retailer-Managed Inventory (RMI) policy and show that the VMI policies significantly reduce the average cost with respect to the RMI policy.