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Die Konstruktionsplanung von neuen Transitrouten oder Energieleitungen auf einem topografischen Gelände wird von Ingenieuren in der Regel manuell vorgenommen, ohne dass eine Optimalität garantiert werden kann. Wir stellen einen neuen Ansatz zur Berechnung von Trajektorien für die Entwicklung neuer optimaler Transitrouten und Energieleitungen zwischen zwei Standorten auf einer Untermannigfaltigkeit U von IR³ vor. Diese Untermannigfaltigkeit repräsentiert die Topographie eines Geländes. U wird näherungsweise durch ein spezielles gewichtetes Gitternetz modelliert. Auf diesem Gitternetz werden die kürzesten Wege für den Bau neuer Routen bestimmt, wobei wir drei Optimierungskriterien betrachten werden: Routen mit minimaler Länge, Routen mit geringsten Baukosten und Routen mit minimalen absoluten Höhenvariationen oder minimalen absoluten Steigungen. Anschließend wird eine Kombination dieser Kriterien gebildet, um dieses Problem zu einem multikriteriellen Optimierungsproblem zu erweitern. Ein Algorithmus für den kürzesten Weg, wie der Dijkstra-Algorithmus, wird verwendet, um optimale Kompromisse für die Konstruktion neuer Routen zu berechnen.
One of the standard approaches for solving time-dependent discrete optimization problems, such as the travelling salesman problem with time-windows or the shortest path problem with time-windows is to derive a so-called time-indexed formulation. If the problem has an underlying structure that can be described by a graph, the time-indexed formulation is usually based on a different, extended graph, commonly referred to as the time-expanded graph. The time-expanded graph can often be derived in such a way that all time constraints are incorporated in its topology, and therefore algorithms for the corresponding time-independent variant become applicable. The downside of this approach is, that the sets of vertices and arcs of the time-expanded graph are much larger than the ones of the original graph. In recent works, however, it has been shown that for many practical applications a partial graph expansion, that might contain time infeasible paths, often suffices to find a proven optimal solution. These approaches, instead, iteratively refine the original graph and solve a relaxation of the time-expanded formulation in each iteration. When the solution of the current relaxation is time feasible an optimal solution can be derived from it and the algorithm terminates. In this work we present new ideas, that allow for the propagation of information about the optimal solution of a coarser graph to a more refined graph and show how these can be used in algorithms, which are based on graph refinement. More precisely we present a new algorithm for solving Mixed Integer Linear Program (MILP) formulations of time-dependent problems that allows for the graph refinement to be carried out during the exploration of the branch-and-bound tree instead of restarting whenever the optimal solution was found to be infeasible. For demonstrating the practical relevance of this algorithm we present numerical results on its application to the shortest path problem with time-windows and the traveling salesman problem with time-windows.
Planning the construction of new transport routes or power lines on terrain is usually carried out manually by engineers, with no guarantee of optimality. We introduce a new approach for the computation of an optimal trajectory for the construction of new transit routes and power lines between two locations on a submanifold U _ R3 representing the topography of a terrain. U is approximatively modeled by a special weighted grid. On this grid, the shortest paths for the construction of new routes are determined, whereby we consider three optimization criteria: routes with minimum distance, routes with lowest construction costs and routes with minimum absolute altitude variations or minimum absolute gradients. Subsequently, a combination of these criteria is used to expand this problem into a multi-criteria optimization problem. A shortest path algorithm, such as the Dijkstra algorithm, is used to compute optimal compromises for the construction of new routes.