Hans-Jürgen Appelrath

Scheduling the supply chain by teams of agents

When a supply chain is established supply chain management (SCM) needs supporting tools for the tasks of operative planning, scheduling, and coordination. These tasks have to be performed not only on the level of the enterprises involved but also within their established business entities (e.g. plants, areas, resource groups, resources) in which the high level schedules have to be put into operation. Most approaches of SCM favor a hierarchical coordination of the supply chain together with powerful algorithmic solutions for the mainly predictive scheduling tasks. These approaches are lacking the incorporation of feedback from lower levels and possibilities of reactive scheduling. Thus flexibility and reactivity are main issues to be improved. We present an approach using teams of cooperating agents in a hierarchical as well as heterarchical way to overcome the problems mentioned. To simplify the generation of such a hierarchy of agents, we develop a framework for scheduling agents that contains the basic features of an agent e.g., event handling, data storage, communication, and possibilities for appending scheduling algorithms and specific cooperation mechanisms. The framework is described and an example illustrates how it is used to build teams of cooperating agents on several levels of the scheduling hierarchy.

The Lower Saxony research network design of environments for ageing: towards interdisciplinary research on information and communication technologies in ageing societies

Worldwide, ageing societies are bringing challenges for independent living and healthcare. Health-enabling technologies for pervasive healthcare and sensor-enhanced health information systems offer new opportunities for care. In order to identify, implement and assess such new information and communication technologies (ICT) the ‘Lower Saxony Research Network Design of Environments for Ageing’ (GAL) has been launched in 2008 as interdisciplinary research project. In this publication, we inform about the goals and structure of GAL, including first outcomes, as well as to discuss the potentials and possible barriers of such highly interdisciplinary research projects in the field of health-enabling technologies for pervasive healthcare. Although GALs high interdisciplinarity at the beginning slowed down the speed of research progress, we can now work on problems, which can hardly be solved by one or few disciplines alone. Interdisciplinary research projects on ICT in ageing societies are needed and recommended.

Multi-site scheduling with fuzzy concepts

Abstract The objective of multi-site scheduling is to support the scheduling activities of a global scheduler and schedulers in distributed production plants in a cooperative way. A global schedule generated on a global level must be translated into detailed schedules as part of the local scheduling process. In case of disturbance, feedback between the local and global levels is essential. Global level data are normally aggregated, imprecise, or estimated. Previous methods focused on local production sites, in most cases without coordination. In this work we present an approach that considers the adequate modeling and processing of imprecise data for global level scheduling within a multi-site scheduling system based on fuzzy concepts. One of the goals is to create a robust prescription for the local scheduling systems which helps to reduce the effort of coordination and rescheduling.

Energy Informatics - Current and Future Research Directions

Due to the increasing importance of producing and consuming energy more sustainably, Energy Informatics (EI) has evolved into a thriving research area within the CS/IS community. The article attempts to characterize this young and dynamic field of research by describing current EI research topics and methods and provides an outlook of how the field might evolve in the future. It is shown that two general research questions have received the most attention so far and are likely to dominate the EI research agenda in the coming years: How to leverage information and communication technology (ICT) to (1) improve energy efficiency, and (2) to integrate decentralized renewable energy sources into the power grid. Selected EI streams are reviewed, highlighting how the respective research questions are broken down into specific research projects and how EI researchers have made contributions based on their individual academic background.

Towards reactive scheduling for large-scale virtual power plants

Concerning distributed energy management, virtual power plants are a frequently discussed topic. Although there are several different approaches to the coordination of distributed energy resources in this context, the inherent dynamics of this complex task especially relating to reactive scheduling have mostly been neglected. As a consequence, this paper discusses MARS, a multiagent-based coordination approach contributing to the solution of the reactive scheduling problem for virtual power plants. Following an introduction to scheduling in the energy domain, a general formalization of scheduling in virtual power plants is given. This formalization is used as starting point for the specification of the control system coordinating the distributed energy resources. Finally, the performance of the resulting domain-specific multiagent system is reviewed by means of simulation.

PROBADO: a generic repository integration framework

The number of newly generated multimedia documents (e.g. music, e-learning material, or 3D-graphics) increases year by year. Today, the workflow in digital libraries focuses on textual documents only. Hence, considering content-based retrieval tasks, multimedia documents are not analyzed and indexed sufficiently. To facilitate content-based retrieval and browsing, it is necessary to introduce recent techniques for multimedia document processing into the workflow of nowadays digital libraries. In this short paper, we introduce the PROBADO-framework which will (a) integrate different types of content-repositories --- each one specialized for a specific multimedia domain --- into one seamless system, and (b) will add features available in text-based digital libraries (such as automatic annotation, full-text retrieval, or recommender services) to non-textual documents. Existing libraries will benefit from the framework since it extends existing technology for handling textual documents with features for dealing with the non-textual domain.

Data Stream Management in the AAL: Universal and Flexible Preprocessing of Continuous Sensor Data

Continuous and potentially infinite sequences of data—so-called data streams—are processed in many applications of Ambient Assisted Living (AAL). The preprocessing of such high frequent data is normally done by fixed code or hard wired hardware. This leads on the one hand to an inflexible and extensive to change processing and on the other hand to very specialized solutions. Like databases data stream management systems (DSMS) offer a universal processing of data, but are designed for highly frequent and potentially infinite data streams. Thus, DSMS are an alternative approach for processing sensor data. Therefore, this paper shows how DSMS can be used in the AAL for an universal and flexible preprocessing of sensor data. For this, DSMS and its features are introduced and we show which advantages over existing solutions a DSMS can offer for future researches in AAL.

Das EUREKA-Projekt PROTOS

Ziel des EUREKA-Projekts PROTOS (Prolog TQOIS for Building Expert Systems) ist die Realisierung integrierter Prolog-Werkzeuge zur Entwicklung von Expertensystemen. Das Projekt gliedert sich in vier Teilprojekte: Prolog-Programmierumgebung Prolog und Datenbanken Konsistenzkonzepte fur Prolog-Systeme Applikationsentwichlung und Werkzeugevaluation

PMCube: A Data-Warehouse-Based Approach for Multidimensional Process Mining

Process mining provides a set of techniques to discover process models from recorded event data or to analyze and improve given process models. Typically, these techniques give a single point of view on the process. However, some domains need to differentiate the process according to the characteristic features of their cases. The healthcare domain, for example, needs to distinguish between different groups of patients, defined by the patients’ properties like age or gender, to get more precise insights into the treatment process. The emerging concept of multidimensional process mining aims to overcome this gap by the notion of data cubes that can be used to spread data over multiple cells. This paper introduces PMCube, a novel approach for multidimensional process mining based on the multidimensional modeling of event logs that can be queried by OLAP operators to mine sophisticated process models. An optional step of consolidation allows to reduce the complexity of results to ease its interpretation. We implemented this approach in a prototype and applied it in a case study to analyze the perioperative processes in a large German hospital.

A Generic Approach for Calculating and Visualizing Differences Between Process Models in Multidimensional Process Mining

Process mining automatically generates process models from event logs. In multidimensional process mining, these models can be analyzed from various viewpoints by clustering event traces according to their attributes, e.g. age or region of the patient for a healthcare process. For each cluster, a distinct process model is calculated. Since these models are supposed to be identical in most parts, differences between them are hard to spot. Therefore, a tool for emphasizing these differences is needed. To face the different challenges presented by multidimensional process mining like the representational bias, such an approach has to be customizable to support different modeling languages and different layout and differencing algorithms. This paper presents a generic approach to calculate and visualize differences between process models which can be used to compare models in multidimensional process mining.