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.