Browsing by Subject "Logistics"

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Entwicklung einer kontextbasierten Systemarchitektur zur Verbesserung des kooperativen Einsatzes mobiler Arbeitsmaschinen
(2018) Steckel, Thilo; Griepentrog, Hans
In contrast to industrial production processes, agricultural processes are characterized by high uncertainty in terms of planning and execution. Main reasons for this are system-induced high environmental exposure, high complexity of the technical systems, a low division of labor and the lack of applicable systems for decision-making and support.Low process transparency and suboptimal decisions result from that. This observation becomes measurable by comparison of installed performance, determined under ideal conditions, and realized performance, determined from literature and telematics data, which are at a level of approximately 40 to 50%. In the present work the causes for this gap are analyzed and a method for their reduction is developed. Key to improving the situation is the systematic use of context-oriented approaches. The context dimensions time, space and system are described and related to each other. In this way, decision-relevant process conditions in agricultural work processes can be described in a structured manner. On the basis of these contexts, components are derived which, in a subsequent system architecture, enable the automated identification, description and evaluation of process contexts. On this basis concrete measures for the improvement of processes can be derived within the scope of the given possibilities (eg machine performance, drivability). The principle of system architecture is exemplified by the example of the harvesting of silo maize (chipping, transport, storage). The process is modeled from a contextual viewpoint and implemented as agent-based simulation, taking into account the above defined components. In order to carry out the simulation, performance (eg. throughput) and cost-relevant (eg. fuel consumption) parameters are recorded on real machines and production functions are developed. The simulation provides the costs and time requirements for a given process configuration (performance of the forage harvester, number, speed and capacity of the transport vehicles as well as number and mass compacting vehicles). In a parameter configuration based on this simulation a solution space is created which can be used to derive advantageous behaviors. Performance-determining parameters in the determined limits and defines step size are used for that. In addition to the simulation, a mathematical method for the generation of logistic characteristics is developed. Simulation and characteristic fields provide the possibility discreet or continuous approaches of the processes. For verification, results are compared with an empirical survey by questioning farmers and contractors. The described approach allows qualified decisions to improve cooperation in processes and thus contribute to the reduction of the abovementioned performance gap. However, the limits of the improvements result from the locally prevailing environmental conditions and must be defined by the user. Further steps for the control and optimization of processes can be developed on the described approach.
Tackling the rich vehicle routing problem with nature-inspired algorithms
(2022) Lesch, Veronika; König, Maximilian; Kounev, Samuel; Stein, Anthony; Krupitzer, Christian; Lesch, Veronika; University of Würzburg, Würzburg, Germany; König, Maximilian; PASS Logistics Solutions AG, Aschaffenburg, Germany; Kounev, Samuel; University of Würzburg, Würzburg, Germany; Stein, Anthony; University of Hohenheim, Hohenheim, Germany; Krupitzer, Christian; University of Hohenheim, Hohenheim, Germany
In the last decades, the classical Vehicle Routing Problem (VRP), i.e., assigning a set of orders to vehicles and planning their routes has been intensively researched. As only the assignment of order to vehicles and their routes is already an NP-complete problem, the application of these algorithms in practice often fails to take into account the constraints and restrictions that apply in real-world applications, the so called rich VRP (rVRP) and are limited to single aspects. In this work, we incorporate the main relevant real-world constraints and requirements. We propose a two-stage strategy and a Timeline algorithm for time windows and pause times, and apply a Genetic Algorithm (GA) and Ant Colony Optimization (ACO) individually to the problem to find optimal solutions. Our evaluation of eight different problem instances against four state-of-the-art algorithms shows that our approach handles all given constraints in a reasonable time.