Model-based decision support for supply chains

Advances in software algorithms, and operations research methods provide the opportunity for effectively modelling decentralised decision making in large-scale systems operating in dynamic, uncertain environments. Computer models typically contain software abstractions with an excellent mapping to real-world entities that can be rapidly assembled and used for predicting system performance under a variety of alternative situations. This paper outlines fundamental issues in modelling and human-centred decision making and presents an interactive system that follows the philosophy of mixed-initiative collaboration where human decision makers and automated agents work together in achieving high joint performance in the context of a supply chain system.