In this research, an integrated inventory problem is formulated for a single-vendor multiple-retailer supply chain that works according to the vendor managed inventory policy. The model is derived based on the economic order quantity in which shortages with penalty costs at the retailers` level is permitted. As predicting customer demand is the most important problem in inventory systems and th...

In this work we investigate two variants of the Stochastic Vehicle Routing Problem: The Vehicle Routing Problem with Stochastic Demands and the Vehicle Routing Problem with Stochastic Demands and Customers. We show that under some moderate conditions there is an asymptotic equivalence between the Vehicle Routing Problem with Stochastic Demands and the Traveling Salesman Problem, as well as betw...

We consider the vehicle routing problem with stochastic demands (VRPSD), a in which customer are known distribution at route planning stage and revealed during execution upon arrival each customer. A long-standing open question on VRPSD concerns benefits of allowing, execution, partial reordering planned visits. Given practical importance this growing interest under optimal restocking, we study...

This article is concerned with the (r, q) inventory model, where demand accumulates continuously, but the demand rate at each instant is determined by an underlying stochastic process. The primary result is the demonstration of a certain insensitivity property, which characterizes the limiting behavior of the model. This property drastically simplifies the computation of performance measures fo...

We solve a rich logistical problem inspired from practice, in which a heterogeneous xed eet of vehicles is used for collecting recyclable waste from large containers over a nite planning horizon. Each container is equipped with a sensor, which communicates its level at the start of the day. Given a history of observations, a forecasting model is used to estimate the point demand forecasts as we...

In this paper, a Stochastic Dynamic Facility Location Problem (SDFLP) is formulated. In the first part, an exact solution method based on stochastic dynamic programming is given. It is only usable for small instances. In the second part a Monte Carlo based method for solving larger instances is applied, which is derived from the Sample Average Approximation (SAA) method.

We consider the vehicle routing problem with stochastic demands (VRPSD). We give randomized approximation algorithms achieving approximation guarantees of 1 + for split-delivery VRPSD, and 2 + for unsplit-delivery VRPSD; here  is the best approximation guarantee for the traveling salesman problem. These bounds match the best known for even the respective deterministic problems [Altinkemer, K...