High tidal ranges pose a significant challenge for affected ports. Waterway locks ensure sufficient water levels but their use often coincides with a loss of water in the harbour basins. As an alternative to energy-intensive pumping stations, it is desirable to fill the port naturally, e.g., by opening the lock gates at high tides. Unfortunately, this is a complex and dynamic scheduling problem due to manifold contributing factors. This paper outlines a novel architecture towards intelligent control for waterway lock operations. The concept employs a multi-agent system to cope with the problem complexity and dynamics. Its software agents represent relevant stakeholders, thereby integrating prediction models derived from machine learning.

This dissertation develops coordination mechanisms for the implementation of autonomous control in logistics with multiagent technology. Therewith, it tackles the challenges of supply network management caused by the complexity, the dynamics, and the distribution of logistics processes. The paradigm of autonomous logistics reduces the computational complexity and copes with the dynamics locally by delegating process control to the participating objects (such as shipping containers). The dissertation specifies and implements the cooperative problem-solving process for autonomous logistics. The presented solution has been used in a realistic simulation of real-world container logistics processes. The validation shows that autonomous control is feasible and that it outperforms the previous centralised dispatching approach by significantly increasing the resource utilisation efficiency.

Manifold approaches exist in the field of similarity-based shape retrieval. Although many of them achieve good results in reference tests, there has been less focus on systematically examining the factors influencing both retrieval performance and computational effort. Such an investigation, however, is important for the structured development and improvement of shape descriptors. This paper contributes a thorough investigation of the influence of the shape part-order and approximation precision. Firstly, two shape descriptors based on qualitative spatial relations are introduced and evaluated. These descriptors are particularly suited for the intended investigation because their only distinction is that one of them preserves the part-order, the other abandons it. Secondly, the recall and precision values are related to the degree of approximation in three-dimensional recall-precision-approximation diagrams. This helps choose an appropriate approximation precision. Finally, it turns out that remarkable retrieval results can be achieved even if only qualitative position information is considered.

The efficiency of conventional centralised control in logistics is limited due to the complexity, the dynamics, and the distribution of logistics processes. The paradigm of autonomous logistics aims at overcoming these limitations by delegating decision-making to local logistics entities such as packages or containers. Represented by software agents, these entities must cooperate with each other to succeed in their logistics objectives. This paper introduces two interaction protocols for team formation of logistics entities. Which of them is adequate depends on the concrete application at hand. This decision is closely related with the limitations of autonomous logistics. One protocol aims at decreasing the communication effort, i.e., increasing the interaction efficiency. The other one aims at increasing the degree of decentralisation. This paper contributes a thorough investigation that supports system developers in choosing the right protocol for their demands.

Cloud computing denotes a paradigm shift in computing that enables a flexible allocation of hardware and software resources on demand. Therewith, it is particularly appealing for applications with a high degree of computational complexity and dynamics. This paper identifies logistics planning and control as a promising application for clouds. However, two prerequisites must be met for cloud-based logistics control. Firstly, the platform-as-a-service layer must provide a synchronisation of the physically distributed real-world material flows and the data flows in the cloud. Secondly, appropriate and scalable control software must be implemented on the software-as-a-service layer. Apart from outlining the technical foundations, this paper describes how both steps enable a business model that is usually referred to as fourth-party logistics.

The objective of logistics is to provide the right quantity of the right objects in the right place at the right time in the right quality for the right price (Jünemann, 1989, p. 18). Its purpose is to provide manufacturing facilities with raw materials and to supply customers with products. Jünemann explicitly points out that minimising costs cannot be the only goal because the other mentioned goals also play an important role in satisfying elaborate logistics demands.

Supply network management is a challenging task due to the complexity, dynamics, and distribution of logistics processes. Delegating process control to intelligent software agents that represent logistics objects and act on their behalf helps approach these challenges. The resulting problem decomposition reduces the computational complexity. Dynamics can be dealt with locally. An important prerequisite for coordinated process control is that agents can cooperate with each other. Based on requirements from logistics, this paper presents an interaction protocol for team formation. A thorough complexity analysis for the proposed method is conducted because the arising interaction effort is not obvious as it depends on the number of teams formed. Therewith, agent developers can estimate the interaction effort and thus the applicability of the method in advance. Finally, an application of the introduced protocol is outlined.

This paper is about the reproduction of ancient texts with vectorised fonts. While for OCR only recognition rates count, a reproduction process does not necessarily require the recognition of characters. Our system aims at extracting all characters from printed historic documents without the employment of knowledge of language, font, or writing system. It searches for the best prototypes and creates a document-specific font from these glyphs. To reach this goal, many common OCR preprocessing steps are no longer adequate. We describe the necessary changes of our system that deals particularly with documents typeset in Fraktur. On the one hand, algorithms are described that extract glyphs accurately for the purpose of precise reproduction. On the other hand, classification results of extracted Fraktur glyphs are presented for different shape descriptors.

Logistics processes in a globalised economy are increasingly complex, dynamic, and distributed. These properties pose major challenges for logistics planning and control. Conventional centralised approaches are frequently limited in their efficiency due to the high number of logistics objects and parameters to be considered. As an alternative, the paradigm of autonomous control in logistics delegates decisionmaking to the participating logistics objects themselves. This allows for decreasing the computational effort and coping with dynamics locally. Implementing autonomous logistics with intelligent software agents makes logistics control flexible and scalable with respect to transient demands. In order to meet customer demands, however, also the underlying hardware platform must be scalable. To this end, this paper examines cloud computing as a hardware platform abstraction for autonomous logistics. It discusses and compares different approaches how cloud computing can facilitate logistics control with intelligent software agents.

This paper deals with transferability of agent implementations from real-world operation to simulation. The objective is to minimise the additional effort for testing and evaluating agent behaviour, mainly arising from the need for synchronisation of simulation time. This can be achieved by incorporating knowledge about agent interaction. An implementation for the FIPA request agent interaction protocol demonstrates the feasibility of this approach.

The concept of multiagent-based simulation introduces the agent programming paradigm to simulation. Multiagent systems ease the implementation of software systems to control complex business processes, such as supply chain management (SCM). Problem complexity is decreased by abolishing monolithic programs. Instead, decision-making is delegated to software agents as local entities. This allows coping even with processes that cannot be controlled centrally due to their inherent physical distribution. Simulation allows evaluating logistics strategies regarding their applicability in such processes. However, general agent development frameworks are not designed to consider simulation-specific issues. In particular, they provide no means for synchronisation. This paper identifies time model adequacy, causality, and reproducibility as quality criteria that must be ensured by a simulation middleware implementing synchronisation. Furthermore, a formal definition of these quality criteria for conservative synchronisation is presented.