1.1 Strategic decisions for autonomous logistics systems

1.1.1 Introduction Logistics management is currently facing major challenges. The integration of the value chain and the growing importance of spatially and organi-sationally distributed production networks strongly increase the need for logistical coordination. Growing customer orientation requires product customization and increased responsiveness in order delivery, thereby raising flexibility and reactivity requirements within the whole supply chain. These developments contribute to the increase in structural and dynamic complexity of logistics systems, thus complicating central planning and control of logistics processes. Research on autonomous cooperating logistics processes confronts these challenges by proposing to replace central planning and control with de-central, autonomous coordination. While former concepts of organisational decentralisation implied an increase in the autonomy of employees, autonomous cooperation in logistics is primarily based on the capability of logistics objects to decide and coordinate themselves. Scholz-Reiter et al. describe the scenario of autonomous cooperation in logistics as follows: " Imagine decentralized distributed architectures of intelligent and communicating objects instead of today's centralized control of non-intelligent objects in hierarchical structures (…). The flow of goods is no longer controlled by a central instance. Instead, the package is finding its way through the transport network to the destination autonomously while constantly communicating with conveyances and nodes and considering demands , e.g. concerning delivery date and costs. " (2004: 358) Autonomous cooperation in logistics promises higher efficiency as well as increased flexibility and robustness even in complex logistics systems. While it is based on the application of several new technologies (cp. Scholz-Reiter et al. 2004), multi-agent technology plays the most promi