A reusable iterative optimization software library to solve combinatorial problems with approximate reasoning

Real world combinatorial optimization problems such as scheduling are typically too complex to solve with exact methods. Additionally, the problems often have to observe vaguely specified constraints of different importance, the available data may be uncertain, and compromises between antagonistic criteria may be necessary. We present a combination of approximate reasoning based constraints and iterative optimization based heuristics that help to model and solve such problems in a framework of C++ software libraries called StarFLIP++. While initially developed to schedule continuous caster units in steel plants, we present in this paper results from reusing the library components in a shift scheduling system for the workforce of an industrial production plant.Comment: 33 pages, 9 figures; for a project overview see http://www.dbai.tuwien.ac.at/proj/StarFLIP

Multisensorielle diskret-kontinuierliche Überwachung und Regelung humanoider Roboter

In der vorliegenden Arbeit wird für eine neue Klasse von humanoiden Robotern ein generisches zweischichtiges diskret-kontinuierliches Regelungskonzept vorgestellt, welches eine operative multisensorielle Überwachung des Roboterumfeldes hinsichtlich störungsbedingter Abweichungen vom geplanten Bewegungsablauf beinhaltet und in der Lage ist, entsprechend zu reagieren. Auf der Grundlage des vorgeschlagenen Konzepts wurden verschiedene perzeptorisch geregelte Grundgeschicklichkeiten implementiert

FLIP++ - A fuzzy logic inference processor library

FLIP++ is a fuzzy logic inference processor library. This C++ library was developed to do calculations with uncertain data and priorities. It evaluates various types of rules of different importance from a hierarchy of rules for uncertain or precise data. It evaluates only those parts of the hierarchy needed for the result. The result itself has two forms: first as a list of membership functions, and second as a crisp value usable for fuzzy control. The library also contains the whole functionality needed to manage one or more sets of rules on all data. It is built to be easily adapted to new applications. Due to its quite general concept of the classes it is possible to include it for the purpose of fuzzy computations in other systems. Please send all correspondence regarding this paper to Wolfgang Slany. 1 FLIP++ as part of a scheduling project FLIP++ is usable as a standalone fuzzy control module together with the user interface from the InterFLIP++ library. Alternatively it ca..

A Methodology for Modelling Mobile Agent-Based Systems (Mobile agent Mobility Methodology - MaMM)

Mobile agents are a particular type of agents that have all the characteristics of an agent and also demonstrate the ability to move or migrate from one node to another in a network environment. Mobile agents have received considerable attention from industry and the research community in recent times due to the fact that their special characteristic of migration help address issues such as network overload, network latency and protocol encapsulation. Due to the current focus in exploiting agent technology mainly in a research environment, there has been an influx of software engineering methodologies for developing multi-agent systems. However, little attention has been given to modelling mobile agents. For mobile agent-based systems to become more widely accepted there is a critical need for a methodology to be developed to address various issues related to modelling mobility of agent . This research study provides an overview of the current approaches, methodologies and modelling languages that can be used for developing multi-agent systems. The overview indicates extensive research on methodologies for modelling multi-agent systems and little on mobility in mobile agent-based systems. An original contribution in this research known as Mobile agent-based Mobility Methodology (MaMM) is the methodology for modelling mobility in mobile agent-based systems using underlying principles of Genetic Algorithms (GA) with emphasis on fitness functions and genetic representation. Delphi study and case studies were employed in carrying out this research