We study the integrated Cutting Stock & Lot Sizing Problem (CS-LSP) for a manufacturer replenishing raw materials from suppliers using capacitated vehicles. Those raw materials can be rectangular panels in two-dimensional case and bars in one-dimension. Replenishment of those raw materials constitutes the lot sizing part : how many capacitated vehicles to order in each period from which supplier, while minimizing the total cost? The transformation of those raw materials into the end items consists in the cutting stock problem : how to cut each panel (or bar) to satisfy the final demand of the customers for different types of items, while minimizing the total number of raw materials used over the given time horizon? Both problems are integrated into the same model to obtain the global optimal solution respecting replenishment cost and constraints together with cutting stock cost and constraints. Note that the replenishment decisions directly impact the assortment of raw materials available in each period when solving the cutting stock problem. We propose a mixed integer linear programming (MILP) formulation for this integrated problem. We also study some special cases by decomposing it into subproblems to use some dynamic programming algorithms already existing in the literature.