Hanne, Thomas
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Optimizing staff rosters for emergency shifts for doctors
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.
On utilizing infeasibility in multiobjective evolutionary algorithms
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.
Some aspects of polytope degeneracy in multicriteria decision making and an outlook
Multiobjective and Preference-Based Decision Support for Rail Crew Rostering
In this paper we discuss a real-life problem in rail crew rostering. Specific emphasis is placed on the requirements of advanced approaches in rostering and the usage of optimization-based decision support. The modeling of the rostering problems is discussed including the treatment of constraints, the consideration of preferences, and the formulation of several objective functions. The specific solving method of the problem using an evolutionary algorithm and visualization and navigation tools for decision support are sketched briefly and some preliminary results are shown. Finally, some conclusions are presented.
Single and Multiobjective Optimization of the Train Staff Planning Problem Using Genetic Algorithms
Bringing robustness to patient flow management through optimized patient transports in hospitals
Fallstudie Swiss Post Solutions / cablecom: Archive as a Service
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.