Fabien Mangione

Optimal configuration of assembly supply chains using analytical target cascading

This paper proposes to apply analytical target cascading (ATC) for configuring assembly supply chains with convergent structures. Individual enterprises in a supply chain are represented as separate elements in an ATC hierarchy. They are able to maintain autonomous and heterogeneous decision systems for optimising their private decision variables and objectives. They collaborate vertically and laterally along the ATC hierarchy through their common decisions to achieve the overall consistency and optimality. ATC offers a competitive balance between computational efficiency and effectiveness while providing an opportunity for parallel computation to further improve the efficiency. This paper also investigates the feasibility for individual enterprises to set local targets while participating in the supply chain configuration (SCC). SCC usually involves discrete decision variables, causing significant difficulties for existing ATC techniques to achieve system consistency. Therefore, a new consistency scheme has to be proposed in this paper, including two techniques: importance weighting factor (IWF) and dynamic constraints (DC). A case study is used to demonstrate the application of the ATC method for solving typical SCC problems. A series of comparative analyses are conducted to identify the strengths of the ATC method and demonstrate the effectiveness of the proposed consistency scheme.

A polynomial time algorithm for the single-item lot sizing problem with capacities, minimum order quantities and dynamic time windows

This paper deals with the single-item capacitated lot sizing problem with concave production and storage costs, considering minimum order quantity and dynamic time windows. The frequency constraints on the production lots are modeled by dynamic time windows. Between two consecutive production lots, there are at least Q periods and at most R periods. This paper presents an optimal algorithm in O ( ( T - Q ) 2 ( R - Q ) T 4 Q 3 ) , which is bounded by O ( T 7 ) .

Optimal repositioning and purchasing policies in returnable container management

This work focuses on the optimization of the returnable container management problem in a global and sustainable supply chain context. The problem consists in: (1) choosing the best way to reposition empty containers between several sites for next rounds of use and (2) purchasing the right quantity of new containers at the right period to meet system requirements for product transportation. For this problem a linear integer program model is proposed. Based on some partial network flow properties (section IV.C), a decomposition into two independent models, purchasing and transportation, has been developed to determine an optimal policy. The benefits of this decomposition, on the technical and industrial level, will be presented and discussed.