Structuring global supply chain networks is a complex decision making process. The typical inputs to such a process consist of a set of customer zones to serve, a set of products to be manufactured, shipped and sold, demand projections for the different customer zones, information about future conditions and costs (e.g. transportation and production) and resources (e.g. capacities, available materials).

We propose a mathematical modeling framework capturing many practical aspects of network design problems simultaneously that have not received adequate attention in the literature. The aspects considered include: dynamic planning horizon, generic supply chain network structure, external supply of materials, inventory opportunities for goods, distribution of commodities, facility configuration, availability of capital for investments, and storage limitations. Moreover, network configuration decisions concerning the gradual relocation of facilities over the planning horizon are considered. To cope with fluctuating demands, capacity expansion and reduction scenarios are also analyzed as well as modular capacity shifts. The relation of the proposed modeling framework with existing models is discussed. For problems of reasonable size we report on our computational experience with standard mathematical programming software. In particular, useful insights on the impact of various factors on network design decisions (like number of time periods) are provided. Moreover, solution approaches are presented using decomposition approaches. Also a specially designed heuristic approach is proposed. The proposed heuristic performs very well on a large set of randomly generated problems. Some of the proposed models have been integrated into commercial software packages. Finally we give a brief overview of some recent research projects where the above mentioned methods have been used.