Of fog and clouds: How are we capable of conducting the computations for near real-time applications?

Narges Mehran, who came to Klagenfurt from Iran in order to pursue her doctoral studies, has specialized in cloud and fog computing as part of her doctoral thesis. These decentralized processing systems make it possible to reduce latency and processing times.

Remarkable success for Mathematics and Statistics at the University of Klagenfurt: funding for 14 new PhD students in the field of optimization in FWF doc.funds project

The approval of this project represents a milestone in the success story of the Departments of Mathematics and Statistics at the University of Klagenfurt. It’s also a great achievement on the part of the participating professors and particularly for the 32-year-old coordinator, Michaela Szölgyenyi. Starting in autumn 2020, the project will employ around one dozen international young scientists in Klagenfurt.

Master’s Thesis: Development of a software environment for an online study in management

Topic

The master thesis will contribute to an experimental research study carried out at the Department of Management Control and Strategic Management. You will work on the platform for an interactive online experiment that involves human decision makers in a laboratory setting. The focus of the experimental study is in the field of task formation in a complex environment.

Timing

As soon as possible upon individual agreement

Prerequisites

Strong programming skills

Supervision of the master thesis

Univ.-Prof. Dipl.-Ing. Dr. Dietmar Jannach
(dietmar [dot] jannach [at] aau [dot] at)

Department of Applied Informatics

Project team

Assoc. Prof. Dr. Alexandra Rausch
(alexandra [dot] rausch [at] aau [dot] at)

Assoc. Prof. Dr. Stephan Leitner
(stephan [dot] leitner [at] aau [dot] at)

Department of Management Control and Strategic Management

IEEE Access Journal Paper: “An Efficient, Scalable and Robust Neuro-Processor Based Concept for Solving Single-Cycle Traveling Salesman Problems in Complex and Dynamically Reconfigurable Graph Networks,”

The authors J. C. Chedjou, K. Kyamakya und N. A. Akwir could publish in the top-class Open Access Journal “IEEE Access” a journal paper with the title: “An Efficient, Scalable and Robust Neuro-Processor Based Concept for Solving Single-Cycle Traveling Salesman Problems in Complex and Dynamically Reconfigurable Graph Networks,”.

Abstract:

We develop, for the first time, and validate through some illustrative examples a new neuro-processor based concept for solving (single-vehicle) traveling salesman problems (TSP) in complex and dynamically reconfigurable graph networks. Compared to existing/competing methods for solving TSP, the new concept is accurate, robust, and scalable. Also, the new concept guarantees the optimality of the TSP solution and ensures subtours avoidance and thus an always-convergence to a single-cycle TSP solution. These key characteristics of the new concept are not always satisfactorily addressed by the existing methods for solving TSP. Therefore, the main contribution of this paper is to develop a systematic analytical framework to model (from a nonlinear dynamical perspective) the TSP, avoid/eliminate subtours, and guarantee/ensure convergence to the true/exact TSP solution. Using the stability analysis (nonlinear dynamics), analytical conditions are obtained to guarantee both robustness and convergence of the neuro-processor. Besides, a bifurcation analysis is carried out to obtain ranges (or windows) of parameters under which the neuro-processor guarantees both TSP solution’s optimality and convergence to a single-cycle TSP solution. In order to validate the new neuro-processor based concept developed, two recently published application examples are considered for both benchmarking and validation as they are solved by using the developed neuro-processor.

More information: https://ieeexplore.ieee.org/document/8995468