We study the applicability of multi-agent systems (MAS) to production and logistics network management. The goal is to create and evaluate sets of intelligent agents that can cooperatively support production and logistics network decisions, as well as to compare their performance to other more traditional methods. A short description of supply chains is given, as well as a formal characterization of the problem space under investigation. We outline a general simulator that allows for a systematic evaluation of different multi-agent approaches across the different parts of this problem space. This is illustrated by a case study on district heating systems. A major concern in this domain is how to cope with the uncertainty caused by the discrepancies between the estimated and the actual customer demand. Another concern is the temporal constraints imposed by the relatively long production and/or distribution times. In the case study we show how to lessen the impact of these problems by the usage of agent clusters and redistribution of resources.