Hanne, Thomas

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Thomas
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Hanne, Thomas

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Gerade angezeigt 1 - 9 von 9
  • Vorschaubild
    Publikation
    A credit rating model in a fuzzy inference system environment
    (MDPI, 2019) Yazdi, Amir Karbassi; Hanne, Thomas; Wang, Yong J.; Wee, Hui-Ming [in: Algorithms]
    One of the most important functions of an export credit agency (ECA) is to act as an intermediary between national governments and exporters. These organizations provide financing to reduce the political and commercial risks in international trade. The agents assess the buyers based on financial and non-financial indicators to determine whether it is advisable to grant them credit. Because many of these indicators are qualitative and inherently linguistically ambiguous, the agents must make decisions in uncertain environments. Therefore, to make the most accurate decision possible, they often utilize fuzzy inference systems. The purpose of this research was to design a credit rating model in an uncertain environment using the fuzzy inference system (FIS). In this research, we used suitable variables of agency ratings from previous studies and then screened them via the Delphi method. Finally, we created a credit rating model using these variables and FIS including related IF-THEN rules which can be applied in a practical setting.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Multilingual Sentiment Analysis for a Swiss Gig
    (27.08.2018) Pustulka, Elzbieta; Hanne, Thomas; Blumer, Eliane; Frieder, Manuel; Wong, Ka Chun [in: 6th International Symposium on Computational and Business Intelligence (ISCBI 2018)]
    We are developing a multilingual sentiment analysis solution for a Swiss human resource company working in the gig sector. To examine the feasibility of using machine learning in this context, we carried out three sentiment assignment experiments. As test data we use 963 hand annotated comments made by workers and their employers. Our baseline, machine learning (ML) on Twitter, had an accuracy of 0.77 with the Matthews correlation coefficient (MCC) of 0.32. A hybrid solution, Semantria from Lexalytics, had an accuracy of 0.8 with MCC of 0.42, while a tenfold cross-validation on the gig data yielded the accuracy of 0.87, F1 score 0.91, and MCC 0.65. Our solution did not require language assignment or stemming and used standard ML software. This shows that with more training data and some feature engineering, an industrial strength solution to this problem should be possible.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Comparison of the behavior of swarm robots with their computer simulations applying target-searching algorithms
    (Engineering and Technology, 2018) Zhong, Jia; Dornberger, Rolf; Hanne, Thomas [in: International Journal of Mechanical Engineering and Robotics Research]
    This paper investigates the functionality and quality of the implementation of a search and target surrounding swarm robotic algorithm using physical swarm robots named Kilobots. The implementation was developed and tested in the simulator V-REP, then transferred onto the actually running Kilobots: Ten Kilobots were used for the experiment, where one Kilobot acts as the target and nine Kilobots act as the searchers. The algorithm allows the searchers to swarm out to find the target while avoiding collisions with other searchers, to orbit around other searchers, which are closer to the target, and finally to surround the target once it is found. The results of the implementation using the physical Kilobots are compared with the results of two adjusted computer simulations. Differences between the simulations and the real robot implementation are investigated: Discrepancies regarding the locomotion and the communication capabilities are identified and discussed.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Finding the best third-party logistics in the automobile industry
    (Hindawi, 2018) Yazdi, Amir Karbassi; Hanne, Thomas; Osorio Gómez, Juan Carlos; García Alcaraz, Jorge Luis [in: Mathematical Problems in Engineering]
    Given the current economic climate, many companies are considering outsourcing some activities to reduce costs and to focus on their core competency; thus, by adopting a competency-focused approach they enhance their chances to survive in a growing and competitive market. Third-Party Logistics (3PL) is a system that facilitates logistic activities. First, however, the organizations need to assess which companies are suitable for outsourcing. The aim of this paper is to depict a structural system for 3PL selection and validate it in real-world automobile companies. We use the Delphi method to determine criteria for 3PL selection and apply Evaluation by an Area-based Method for Ranking (EAMR) to prioritize the candidate alternatives. This method is used in combination with a Shannon Entropy based approach for determining the required weights. Computational analysis shows which criteria and companies have high priority, and based on that candidate alternatives for outsourcing are evaluated. The results suggest how automobile companies select 3PL companies and allocate their work to them.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Gaussian guided self-adaptive wolf search algorithm
    (MDPI, 2018) Song, Qun; Fong, Simon; Deb, Suash; Hanne, Thomas [in: Entropy]
    Nowadays, swarm intelligence algorithms are becoming increasingly popular for solving many optimization problems. The Wolf Search Algorithm (WSA) is a contemporary semi-swarm intelligence algorithm designed to solve complex optimization problems and demonstrated its capability especially for large-scale problems. However, it still inherits a common weakness for other swarm intelligence algorithms: that its performance is heavily dependent on the chosen values of the control parameters. In 2016, we published the Self-Adaptive Wolf Search Algorithm (SAWSA), which offers a simple solution to the adaption problem. As a very simple schema, the original SAWSA adaption is based on random guesses, which is unstable and naive. In this paper, based on the SAWSA, we investigate the WSA search behaviour more deeply. A new parameter-guided updater, the Gaussian-guided parameter control mechanism based on information entropy theory, is proposed as an enhancement of the SAWSA. The heuristic updating function is improved. Simulation experiments for the new method denoted as the Gaussian-Guided Self-Adaptive Wolf Search Algorithm (GSAWSA) validate the increased performance of the improved version of WSA in comparison to its standard version and other prevalent swarm algorithms.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Vorschaubild
    Publikation
    Gig work business process improvement
    (CPS, 2018) Pustulka, Elzbieta; Telesko, Rainer; Hanne, Thomas; Wong, Ka Chun [in: ISCBI 2018. 6th International Symposium on Computational and Business Intelligence. Proceedings]
    We collaborate with a gig work platform company (GPC) in Switzerland. The project aims to improve the business by influencing process management within the GPC, providing automated matching of jobs to workers, improving worker acquisition and worker commitment, and particularly focusing on the prevention of no shows. One expects to achieve financial, organizational and efficiency gains. As research tools we use a combination of text mining and sentiment analysis, Business Process Modeling and Notation (BPMN), interviews with workers and employers, and the design of sociotechnical improvements to the process, including platform improvements and prototypes. Here, we focus on the successful combination of BPMN modelling with sentiment analysis in the identification of problems and generation of ideas for future modifications to the business processes.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Die Biologie als Wegweiser
    (Swiss Professional Media, 10/2017) Hanne, Thomas [in: Unternehmer Zeitung]
    KÜNSTLICHE INTELLIGENZ. Seit etwa zehn Jahren erlebt die Erforschung künstlicher Intelligenz eine Renaissance, die vor allem durch die zunehmende Nutzung von Online-daten vorangetrieben wird. Die Erkenntnisse können für Prozesse der Logistik vielfältig genutzt werden.
    01B - Beitrag in Magazin oder Zeitung
  • Vorschaubild
    Publikation
    On utilizing infeasibility in multiobjective evolutionary algorithms
    (Springer, 2009) Hanne, Thomas; Barichard, Vincent; Ehrgott, Matthias; Gandibleux, Xavier; T'Kindt, Vincent [in: Multiobjective programming and goal programming. Theoretical results and practical applications]
    In this article, we consider the problem of infeasible solutions (i.e. solutions which violate one or several restrictions of an optimization problem) which can hardly be avoided when new solutions are generated by stochastic and other means during the run of an optimization algorithm. Since typical approaches for dealing with infeasibility such as using a repair mechanism, a punishment approach, or a simple recalculation of solutions are not fully satisfying in many problems, we suggest a new approach of tolerating and actively using infeasible solutions within the framework of multiobjective evolutionary algorithms. The novel evolutionary algorithm allows solving a multiobjective optimization problem (MOP) with continuous variables by approximating the efficient set. The algorithm uses populations of variable size and new rules for selecting solutions for the subsequent generations. In particular, some of the selected solutions may be infeasible such that the Pareto front is approached at the same time from two sides, the feasible set and a subset of the infeasible set. Since the considered in feasible solutions correspond to a dual optimization problem, we call the new algorithm primaldual multiobjective optimization algorithm, or PDMOEA. The algorithm is demonstrated by considering a numerical test problem and is compared with two other approaches for dealing with infeasibility. The example shows a specific strength of the new approach: By tunneling through infeasible regions, the population may more easily extent to new separated parts of the Pareto set.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Fallstudie Swiss Post Solutions / cablecom: Archive as a Service
    (Hanser, 2008) Hanne, Thomas; Wölfle, Ralf; Schubert, Petra [in: Wettbewerbsvorteile in der Kundenbeziehung durch Business Software]
    Diese Fallstudie beschreibt eine elektronische Archivierungslösung für Rechnungen. Der Schweizer Kabelnetzbetreiber cablecom GmbH nutzt hierzu die Dienste des Business Process Outsourcing-Dienstleisters Swiss Post Solutions AG. Besonderheiten der Archivierungslösung sind der Archivzugriff durch cablecom-Kunden und -Mitarbeiter über eine Weblösung sowie die rechtskonforme Archivierung mittels elektronischer Signatur. Vorteile für cablecom lagen in der schnellen und kostengünstigen Realisierbarkeit der Archivierungslösung bei gleichzeitig hohem Qualitätsniveau, etwa in Bezug auf Sicherheit und Verfügbarkeit.
    04A - Beitrag Sammelband