Abstract
Today’s logistical networks are characterized by a high complexity and lots of interdependencies within and between supply chains. To handle this, strategic Decision Support Systems (DSS) help to make product flows transparent and to get an impression of the consequences of alternative net configurations before a decision is implemented. Nowadays DSS mainly focus on transportation flows and neglect detailed aspects of warehouse nodes when configurating logistical networks. But especially the interactions between transport and warehouse flows are of high importance for plausible results that resist implementation in practice. Therefore an integrated modelling of warehouse and transport processes is necessary. In this paper the Modular Node Model is introduced. Influences and consequences of alternative network decisions on warehouse processes and flows are modelled as well as feed backs to the transportation flows. This rather descriptive model serves as groundwork for optimisation algorithms. The focus lies on identifying relevant influence and decision criteria and developing a method to model relevant interactions. “Optimisation” is only considered in terms of the scenario technique. The model approach decomposes complex strategic decision problems in smaller manageable subproblems. This is done by building separate modules that are connected to each other by interfaces. The practicability of the model is verfied on the basis of an example from the consumer goods industry
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