Maxime Ogier

Decentralised planning coordination with quantity discount contract in a divergent supply chain

This paper proposes to solve a supply chain planning problem with realistic features. The problem consists of planning productions, transportations and storage activities in a supply chain at a tactical level on a finite horizon. The main features considered are decentralised decision making and iteration of the planning process on a rolling horizon basis. In each planning process, the actors optimise their local planning and coordinate to achieve a good overall planning. A multi-agent system is used to model such supply chain behaviour. The study is conducted in a divergent two-echelon supply chain with one manufacturer and multiple independent retailers. Coordination is achieved using a standard contract in practice, known as the ‘quantity discount’ contract. The planning framework on the supply chain structure is detailed. Lot-sizing models integrating the quantity discount are presented for the local planning problems. Experimental tests are conducted with three major parameters: quantity discount price, quantity discount breakpoint and rolling horizon length. They are used to determine the quantity discount parameters in achieving the best supply chain profit, and to analyse the increasing profit of the actors. A decision-making tool which is able to consider realistic features of supply chain planning is therefore resulted.

Service network design in short and local fresh food supply chain

This paper aims at developing efficient solving methods for an original service network design problem imbued with sustainable issues. Indeed the network has to be designed for short and local supply chain and for fresh food products. The original features of the problem are the seasonality of supply, the limitation of transshipments for a product and no possibility of storage between consecutive periods. Decisions at strategic and tactical level are (1) decisions on a subset of hubs to open among a given set of potential locations, (2) transportation services to open between the actors and (3) flow quantities for the fresh food products. We propose for this problem a Mixed Integer Programming formulation and two solving techniques: Benders Decomposition and Dynamic Slope Scaling Procedure. These techniques are adapted to the problem and some experimental tests are conducted in order to compare the approaches on large-scale instances.