Catálogo de publicaciones - libros

Outsourcing (subcontraction) makes use of external entities as an alternative to the usage of own resources (self-fulfillment). The arising ‘make-or-buy’ decision combining the two clusters of self-fulfillment and subcontraction evolves in a complex reference analysis among items involved [13].

We analyze investment incentives of goal incongruent performance measures in an experiment in which ‘managers’ make one-period investment decisions and ‘owners’ predict these decisions. Three alternative performance measures are considered: earnings, ROI, and residual income. These measures serve as archetypes for a wide variety of measures used in practice. Standard theoretical predictions with respect to the investment incentives of earnings, ROI, and residual income are well documented, and they have become part of the management accounting education (e.g., [5]). They illustrate one of the basic principles of management accounting: ‘you get what you pay for’. As is well known, neither earnings nor ROI is a goal congruent performance measure, whereas residual income is goal congruent due to its conservation property.

Management simulation allows students to apply their theoretical knowledge in a safe, feedback-learning context. The quality of the simulation model is important for the achievable learning effect. A model always simplifies reality, but should still strive for a realistic implementation of key factors and relationships of the modeled situation. Vague information and qualitative relationships have a great significance in practical business. In management games, however, such qualitative aspects are often excluded from the simulation as it is difficult to model them adequately [1]. Concepts like “competence”, “image” and “credit rating” are meaningful to business, but difficult to grasp with conventional simulation modeling. In our contribution an approach based on fuzzy sets is presented to help overcoming these difficulties.

Creating a movie shoot schedule is an important part of the movie production process. Even for a small movie project already 50 activities requiring 130 resources such as different actors, director, team, special effects and locations etc. have to be scheduled respecting complex constraints which may be imposed on single resources as well as on every activity.

Maintaining logical consistency in a knowledge base that receives asynchronous events from collaborative agents poses a challenge, due to multiple agent perspectives of the knowledge base. Facades and filters further complicate this problem by distorting the definition of consistent knowledge. Therefore, maintaining logical consistency of the knowledge base requires an infrastructure for handling truth maintenance. This paper presents a generic, object-oriented framework for truth maintenance in collaborative multi-agent systems. The core of the framework is an agent that autonomously reasons on system events, thus guaranteeing the integrity of the knowledge base independent of external agents. Specialization to a particular domain is achieved through the description of tests that verify the consistency of the knowledge base. This paper shows an example of this approach in a real-world, multi-agent system and discusses performance and maintainability in such a system.

Contributing to transparency and traceability of decision making processes and taking into account the preferences of the decision makers, multi-criteria decision analysis (MCDA) is suitable to bring together knowledge from different disciplines and fields of expertise. The modelling of the decision makers’ preferences is a crucial part of any multi-criteria analysis. In multi-attribute value theory (MAVT), preferential information is modelled by weighting factors (i.e. inter-criteria comparisons) and value functions (i.e. intra-criteria preferences). However, the uncertainties associated with the determination of these preferential parameters are often underestimated. Thus, the focus of this paper is the description of an approach to explore the impact of simultaneous variations of these subjective parameters. Special attention is paid to the consideration of variations of the value functions’ shapes. The aim of the presented methods is to facilitate the process of preference modelling and to comprehensibly visualise and communicate the impact of the preferential uncertainties on the results of the decision analysis.

The outranking analysis has been frequently used to deal with the complex decisions involving qualitative criteria and imprecise data (see [5]).

The number of objectives in a multiobjective optimization problem strongly influences both the performance of generating methods and the decision making process in general. On the one hand, with more objectives, more incomparable solutions can arise, the number of which affects the generating method’s performance. On the other hand, the more objectives are involved the more complex is the choice of an appropriate solution for a (human) decision maker. In this context, the question arises whether all objectives are actually necessary and whether some of the objectives may be omitted; this question in turn is closely linked to the fundamental issue of conflicting and non-conflicting optimization criteria. Besides a general definition of conflicts between objective sets, we here introduce the $$ \mathcal{N}\mathcal{P} $$ -hard problem of computing a minimum subset of objectives without losing information ( MOSS ). Furthermore, we present for MOSS both an approximation algorithm with optimum approximation ratio and an exact algorithm which works well for small input instances. We conclude with experimental results for a random problem and the multiobjective 0/1-knapsack problem.

Der Grundstein für eine erfolgreiche Ersatzteil-Lagerlogistik wird mit der Entscheidung über die passenden Lagersysteme gelegt. In der Praxis konkurrieren dabei multiple Zielsetzungen wie z.B. ein zu maximierender Automatisierungsgrad mit den resultierenden zu minimierenden Investitionen. Der Beitrag stellt ein multikriterielles Entscheidungsmodell vor, das speziell im Ersatzteilbereich die Auswahlproblematik anhand von Kennzahlen strukturiert und Möglichkeiten zur Entscheidungsunterstützung anbietet. Zum Einsatz kommt ein dreistufiges Modell auf Grundlage des Analytic Hierarchy Process, das mit Hilfe der Software Expert Choice die Eignung verschiedener Alternativen in unterschiedlichen Lagerzonen ermitteln kann. In Abhängigkeit der zugrunde liegenden Teilestruktur des betrachteten Unternehmens werden zunächst in Frage kommende Lagersysteme ausgewählt und anschließend mit Hilfe des Modells bewertet. Eine Sensitivitätsanalyse sichert die Stabilität des Ergebnisses ab.

In this paper we propose an automatic method for spectral clustering of weighted directed graphs. It is based on the eigensystem of a complex Hermitian adjacency matrix H_ n × n . The number of relevant clusters is determined automatically. Nodes are assigned to clusters using the inner product matrix S_ n × n calculated from a matrix R_ n × l of the l eigenvectors as column vectors which correspond to the positve eigenvalues of H . It can be shown that by assigning the vertices of the network to clusters such that a node i belongs to cluster p _c if Re $$ {\text{(}}S_{i,p_c } {\text{)}} $$ = max _j Re ( S _i,j) an good partitioning can be found. Simulation results are presented.