Institut für Wirtschaftsinformatik

Dauerhafte URI für die Sammlunghttps://irf.fhnw.ch/handle/11654/66

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Gerade angezeigt 1 - 10 von 19
  • Publikation
    Attraction and diffusion in nature-inspired optimization algorithms
    (Springer, 15.05.2015) Yang, Xin-She; Deb, Suash; Hanne, Thomas; He, Xingshi
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Publikation
    Genetic algorithm with embedded Ikeda map applied on an order picking problem in a multi-aisle warehouse
    (09.12.2014) Stauffer, Michael; Ryter, Remo; Davendra, Donald; Dornberger, Rolf; Hanne, Thomas
    04B - Beitrag Konferenzschrift
  • Publikation
    04B - Beitrag Konferenzschrift
  • Publikation
    Optimizing staff rosters for emergency shifts for doctors
    (IEEE, 28.06.2009) Frey, Lukas; Hanne, Thomas; Dornberger, Rolf
    The creation of staff rosters for emergency shifts for doctors is a complex task. To construct good rosters, many restrictions (e.g. holydays and workload) have to be taken into account. These restrictions have been mathematically specified for a concrete case in order to solve the problem afterwards with a straightforward genetic algorithm. Thereby the main focus lays on two different mutation methods and the combination of them. The results of this procedure will be discussed in this work.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Fallstudie Swiss Post Solutions / cablecom: Archive as a Service
    (Hanser, 2008) Hanne, Thomas; Wölfle, Ralf; Schubert, Petra
    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
  • Publikation
    Optimization of the Picking Sequence of an Automated Storage and Retrieval System (AS/RS)
    (11.07.2014) Dornberger, Rolf; Hanne, Thomas; Ryter, Remo; Stauffer, Michael
    06 - Präsentation
  • Publikation
    Index Tracking with Invasive Weed Optimization
    (27.09.2014) Affolter, Konstantin; Dornberger, Rolf; Hanne, Thomas; Schweizer, Daniel
    06 - Präsentation
  • Vorschaubild
    Publikation
    On utilizing infeasibility in multiobjective evolutionary algorithms
    (Springer, 2009) Hanne, Thomas; Barichard, Vincent; Ehrgott, Matthias; Gandibleux, Xavier; T'Kindt, Vincent
    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
  • Publikation
    The Way to an Open-Source Software for Automated Optimization and Learning - Open Opal
    (27.09.2010) Dornberger, Rolf; Hanne, Thomas; Frey, Lukas
    An optimization framework combines various methods, strategies, and programming interfaces on a robust software platform. Its development requires knowledge from application areas, and about optimization methods, as well as from software engineering. Different persons provide diverse know-how about modeling and simulating engineering and/or business problems, about search and optimization methods, and about new software trends to implement them into software. This paper describes the approach how an optimization framework based on evolutionary algorithms and other methods is developed in subsequent projects with application engineers and software developers cooperatively working together guaranteeing a sophisticated knowledge transfer. Therefore, particular knowledge management aspects are emphasized. As result, the optimization platform OpenOpal and the ideas behind its software architecture, supporting the know-how transfer, are presented. In order to continuously improve this optimization framework it is transferred into an open-source software initiative. The objective is to broaden the user group by increasing the number of knowledge contributors both from academia - integrating and testing newly developed optimization methods - and from various engineering areas - providing real-world problems to be solved.
    04B - Beitrag Konferenzschrift