BWL, insb. Wirtschaftsinformatik

Da sich die Entwicklung von E-Government in Deutschland seit Jahren in einer Stagnation befand, verabschiedete die Bundesregierung im Jahr 2013 das sogenannte E-Government-Gesetz, flankiert von unterschiedlichen Initiativen. In den Jahren zuvor hatte sich im Bereich der Informationstechnologie mit Enterprise-Content-Management-Systemen eine neue Art von Plattform etabliert, die sich insbesondere zur Abbildung dokumentengestützter Prozesse und somit auch der digitalen Verwaltung nutzen lässt. Die Einführung eines solchen Systems im Zusammenhang mit einer Umgestaltung der Organisation hin zu einer durchgreifenden Digitalisierung ist ein komplexes Projekt mit vielen Wechselwirkungen. Da bürokratische Organisationen durch grundsätzlich vergleichbare Wirkmechanismen gekennzeichnet sind, wird in dieser Arbeit ein Rahmenmodell entwickelt, das die Einführung von Enterprise-Content-Management-Systemen in bürokratische Organisationen zum Zwecke einer elektronischen Verwaltungsarbeit umfassend abbildet und somit zur Vereinfachung, Standardisierung und Koordinierung dieser Projekte beitragen soll. Aufbauend auf rechtlichen Rahmenbedingungen, vergleichbaren Rahmenmodellen anderer Problemklassen und unter Nutzung von Expertenwissen sowie Nutzervorstellungen wird in dieser Arbeit unter Zuhilfenahme der Design-Science-Forschungsmethodik ein entsprechendes Rahmenmodell als Artefakt entwickelt, vorgeschlagen und anschließend im Rahmen einer Fallstudie empirisch evaluiert.

Recently, new benchmark instances (MMLIB) have been presented by Van Peteghem and Vanhoucke (2014). These instances have been designed in such way that the well known pre-processing procedure of Sprecher et al. (1997) does not have any impact on any instance. We developed a technique that could be applied to the new data set to reduce the number of modes per activity. Computational results show that the procedure is highly effective in reducing the number of modes. A reduction was possible for 2,026 of the 4,320 MMLIB instances.

Battery electric freight vehicles have the potential to mitigate the local urban road freight transport emissions, but their numbers are still insignificant. Logistics companies often consider electric vehicles as too costly compared to vehicles powered by combustion engines. The current literature suggests that increasing the mileage can maximize the competitiveness of electric freight vehicles. In this manuscript we develop a generic model to determine the cost-optimal balance between a high utilization of electric freight vehicles – which often have low operational costs – and their required expensive battery replacements. Our work relies on empirical findings of the real-world energy consumption from a large German field test with vehicles of 7.5 and 12 tons, respectively. Our results suggest that increasing the range to the technical maximum by intermediate (quick) charging and multi-shift usage is not the most cost-efficient strategy in every case. A low daily mileage is more cost-efficient at high energy prices or consumptions, relative to the diesel prices or consumptions, or if the battery is not safeguarded by a long battery warranty. In practical applications our model may help companies to choose the most suitable electric vehicle for the application purpose, or the optimal trip length from a given set of options. For policymakers, our analysis provides insights on the relevant parameters that may either reduce the cost-gap at lower daily mileages, or increase the utilization of electric urban freight vehicles, in order to abate the negative impact of urban road freight transport on the environment.

In this work we consider the Coach Trip with Shuttle Service Problem (CTSSP), which is a routing problem where passengers have to be transported from bus stops to a central hub with a fleet of coaches and shuttles. The capacity of each vehicle must not be exceeded and for each group of passengers waiting at a bus stop there is a maximal travel time that must not be exceeded while travelling to the hub. Shuttles can use bus stops as transfer points to drop their passengers from which they have to be picked up by a coach. Coaches must end their trip at the hub while shuttles can stop at any bus stop. The goal is to minimize costs. The costs consist of travelling costs of the used vehicles plus fixed costs for the usage of the shuttles. We prove the computational complexity of the problem and present a novel mathematical model for the CTSSP. This model is implemented in CPLEX and the optimal solution of the "example" instance of the VeRoLog Solver Challenge 2015 is shown.

Decision making in operational planning is increasingly affected by conflicting interests of different stakeholders such as subcontractors, customers, or strategic partners. Addressing this, automated negotiation is a well-suited mechanism to mediate between stakeholders and search for jointly beneficial agreements. However, the outcome of a negotiation is strongly dependent on the applied negotiation protocol defining the rules of encounter. Although protocol design is well discussed in literature, the question on which protocol should be selected for a given scenario is little regarded so far. Since negotiation problems and protocols are very diverse, the protocol choice itself is a challenging task. In this study, we propose a decision support system for negotiation protocol selection (DSS-NPS) that is based on a machine learning approach – an artificial neural network (ANN). Besides presenting and discussing the system, we, furthermore, evaluate the design artifact in elaborate computational experiments that take place in an intercompany machine scheduling environment. Our findings indicate that the proposed decision support system is able to improve the outcome of negotiations by finding adequate protocols dynamically on the basis of the underlying negotiation problem characteristics.

The increasing coupling of planning and scheduling between different companies leads to novel challenges in devising and implementing effective decision support systems. In this paper, we describe a hard decentralized scheduling problem with heterogeneous machines and competing job sets that belong to different self-interested stakeholders (agents). These agents want to minimize their costs that consist of individual tardiness cost as well as their share of the machine operating cost. The determination of a beneficial solution, i.e., a respective contract in terms of a common schedule, is particularly difficult due to information asymmetry and self-interested behavior of the involved agents. To solve this coordination problem, we present two automated negotiation protocols with a set of optional building blocks. In the first protocol, new solutions are iteratively generated as mutations of a single provisional contract and proposed to the agents, while feasible rules with quotas restrict the acceptance decisions of the agents and, thus, the successive adaptation of the provisional contract. The second protocol is based on a population of contracts and mimics evolutionary processes. For evaluation purposes, we built a simulation testbed and conducted computational experiments. The computational study shows that the protocols can achieve high quality solutions very close to results from centralized multi-criteria procedures. Particular building block configurations yield improved outcomes, e.g., in case that the agents are also allowed to make contract proposals. Thus, the presented approach contributes to the methodology and practice of collaborative decision making.

Für Kurier-, Express- und Paketdienste (KEP-Dienste) stellt die Gestaltung der logistischen Abläufe einen zentralen Erfolgsfaktor dar. Es ergeben sich vielfältige strategische, taktische und operative Planungsaufgaben. In der taktischen Planung sind u.a. depotbezogen die Tourgebiete für den Nahverkehr zu planen und für den Transport der Sendungen im Fernverkehr ein Linienfahrplan zu erstellen. Diese Arbeit betrachtet die Linienverkehrsplanung. Als Fallstudie liegen die Netze und Sendungsdaten europaweit tätiger KEP-Dienstleister zugrunde. Nach einer Darstellung der Planungsaufgabe wird ein heuristischer Lösungsansatz beschrieben, der zentrale Aspekte der praktischen Fallstudien berücksichtigt und mit geringen Rechenzeiten hochwertige Lösungen erzielt.

This doctoral thesis deals with the simulation of urban traffic on a computer system which will be controlled by traffic lights. The management of urban traffic will become more diffcult because of the increase of the amount of vehicle traffic. The modeling of the urban traffic occurs by its simulation and regulation with methods of the Petri net theory. Not only the traffic flow but also its regulation with traffic lights have been realized. The possibilities of coordination of the traffic lights to obtain a better traffic flow will also be shown. The result is an allocation of green time of the traffic lights to improve the vehicle flow and to reduce the waiting time of them.