The vehicle routing problem
A Decomposition Approach to the Inventory Routing Problem with Satellite Facilities
Transportation Science
Deliveries in an Inventory/Routing Problem Using Stochastic Dynamic Programming
Transportation Science
Dynamic Programming Approximations for a Stochastic Inventory Routing Problem
Transportation Science
A simulation framework for real-time management and control of inventory routing decisions
Proceedings of the 38th conference on Winter simulation
Scenario Tree-Based Heuristics for Stochastic Inventory-Routing Problems
INFORMS Journal on Computing
A probabilistic heuristic for a computationally difficult set covering problem
Operations Research Letters
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In this paper, we introduce a simulation-based algorithm for solving the single-period Inventory Routing Problem (IRP) with stochastic demands. Our approach, which combines simulation with heuristics, considers different potential inventory policies for each customer, computes their associated inventory costs according to the expected demand in the period, and then estimates the marginal routing savings associated with each customer-policy entity. That way, for each customer it is possible to rank each inventory policy by estimating its total costs, i.e., both inventory and routing costs. Finally, a multi-start process is used to iteratively construct a set of promising solutions for the IRP. At each iteration of this multi-start process, a new set of policies is selected by performing an asymmetric randomization on the list of policy ranks. Some numerical experiments illustrate the potential of our approach.