A Robust Approach for the Joint Lot-Sizing and Supplier Selection

EasyChair Preprint 2504, version 2

Abstract

With the rise of mass customization, companies tend to increase the number of finished products offered to their customers. As the large number of finished products leads to large inventory costs, these firms commonly adopt the assemble-to-order (ATO) strategy,  where the components are assembled to end-items only when customers order the products. As the ATO strategy matches the end-item assembly with the demand, there is no need to manage the end-item inventory. Conversely, managing the stock of components appropriately is crucial, to assemble on-time without escalating inventory costs. Managing the component's stock is complex, because the assembly site is often close to the customer demands, whereas components are shipped from various locations, and the supplier's delivery lead times are often long and unpredictable (Hsu et al., 2006). Consequently, there is a need to develop purchase planning methods that are robust to uncertain lead times.

In this work, we investigate the situation of a company that pre-selected a set of suppliers for a given component and must place the orders based on the prices and delivery lead times offered by the suppliers. In other words, we aim to provide robust optimization approaches to decide when to order, how much to order, and from which suppliers, in the context of uncertain delivery lead time.

Keyphrases: Lead time uncertainty, Lot-sizing, Supplier selection, robust optimization

@booklet{EasyChair:2504,
  author    = {Simon Thevenin and Oussama Ben Ammar and Nadjib Brahimi},
  title     = {A Robust Approach for the Joint Lot-Sizing and Supplier Selection},
  howpublished = {EasyChair Preprint 2504},
  year      = {EasyChair, 2020}}