Motivation

Logistics is concerned with the organization and control of processes in space and time in order to transport or manufacture goods and the coordination of the resulting flows of material and information, as well as monetary flows. Complexity and dynamics of logistic networks have reached a level that more and more prevents the processes from being entirely observable and fully controllable, caused by, e.g., a globalized economy, a shift from buyer’s to seller’s markets, and shorter product life cycles. Thus, recent trends in logistics point towards solutions with distributed and self-organizing processes.

Such logistic networks are characterized by a wide variety of heterogeneous properties, constraints, and requirements: temporal (very quickly, just in time), economic (low cost, given budget), physical (smooth, secure travel), informational (public, secure data), environmental (low energy, ecology-preserving). Different qualities or modalities need different representations; transitions between different subsystems require interfaces between different representations, transformations of processes, and methods for their selection; knowledge about situations and goals is crucial for the selection of the most suitable strategy; etc. This manifold set of demands and the emerging uncertainty requires the inclusion of methods from artificial intelligence and cognitive science. AILog-2010 addresses the use of these AI methods in modern logistics.