Cooperative uncertain temporal reasoning for distributed transportation scheduling

Transportation scheduling application consists of distributed transportation companies that have to carry out transportation orders which arrive dynamically. Each company has a set of trucks at their disposal. Each company should maximize the satisfaction of orders according to the availability of its trucks. The distributed AI approach is suitable for this application because of: first the complexity of a centralized scheduling algorithm and second the distributed nature of the application (companies and trucks are geographically distributed). Furthermore, the task of transportation is characterized by a high level of uncertainty regarding different factors such as the traffic density, the power of the truck used and soon that cannot be ignored. We present a suitable temporal representation of trucks taking the uncertainty of their availability into account by using the Fuzzy Characteristics Functions and an Extended Contract Net Protocol based on this representation to negotiate the delegation of orders from one company to another one.