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Description: This diploma thesis deals with the restoration problem in telecommunication networks. The goal is to find a cost minimal capacity capacity assignment on the edges and nodes of a network such that given demands can be satisfied even in case of the failure of an edge or node in the network. Moreover, restrictions on the routing paths (like length restrictions) and hardware constraints have to be satisfied. A Mixed Integer Programming model is presented which takes into account restoration requirements as well as hardware constraints and which abstracts from a particular restoration protocol and failure situation. This abstraction provides new insight into the structure of the network restoration problem and shows that from a mathematical point of view, the commonly used restoration techniques Link Restoration, Path Restoration and Reservation are not as different as they seem to be from a practical point of view. In addition, our model allows (but is not limited to) optimizing working capacity, intended for normal use, and spare capacity, intended for rerouting purposes in case of a failure, in one step. Furthermore, our formulation of capacity cost allows taking into account the effects of discrete, non-linear cost structures which are common in practice. Up to our knowledge, no publication in the existing literature covers all these aspects, let alone in one model, although they are of major practical interest. The model has been implemented in a Branch and Cut framework. The theoretical background of the algorithmic procedure is presented in detail, including computational complexity investigations on the pricing problem. The abstraction from a particular restoration protocol turns out to be useful both from a theoretical and computational point of view. In fact, our investigations suggest a distinction into Local Restoration and Global Restoration rather than into Link Restoration,Path Restoration, Reservation and mixtures of these concepts. In addition to the theoretical aspects of the algorithmic procedure, some implementational details are briefly discussed. Our implementation has been tested on 14 real world instances, which is described in detail. One part of the computational results consists of a comparison of optimal network cost values using diffeent restoration mechanisms, applied to securing either all single node failures, all single edge failures or both. In addition, the effects of a discrete cost structure are investigated, which has rarely been considered yet in literature. Furthermore, the cost ifference between joint and successive working and spare capacity optimization is investigated. In the second part of the computational results, several heuristics for the network restoration problem are compared with respect to both solution quality and time. This diploma thesis deals with the restoration problem in telecommunication networks. The goal is to find a cost minimal capacity capacity assignment on the edges and nodes of a network such that given demands can be satisfied even in case of the failure of an edge or node in the network. Moreover, restrictions on the routing paths (like length restrictions) and hardware constraints have to be satisfied. A Mixed Integer Programming model is presented which takes into account restoration requirements as well as hardware constraints and which abstracts from a particular restoration protocol and failure situation. This abstraction provides new insight into the structure of the network restoration problem and shows that from a mathematical point of view, the commonly used restoration techniques Link Restoration, Path Restoration and Reservation are not as different as they seem to be from a practical point of view. In addition, our model allows (but is not limited to) optimizing working capacity, intended for normal use, and spare capacity, intended for rerouting purposes in case of a failure, in one step. Furthermore, our formulation of capacity cost allows taking into account the effects of discrete, non-linear cost structures which are common in practice. Up to our knowledge, no publication in the existing literature covers all these aspects, let alone in one model, although they are of major practical interest. The model has been implemented in a Branch and Cut framework. The theoretical background of the algorithmic procedure is presented in detail, including computational complexity investigations on the pricing problem. The abstraction from a particular restoration protocol turns out to be useful both from a theoretical and computational point of view. In fact, our investigations suggest a distinction into Local Restoration and Global Restoration rather than into Link Restoration, Path Restoration, Reservation and mixtures of these concepts. In addition to the theoretical aspects of the algorithmic procedure, some implementational details are briefly discussed. Our implementation has been tested on 14 real world instances, which is described in detail. One part of the computational results consists of a comparison of optimal network cost values using different restoration mechanisms, applied to securing either all single node failures, all single edge failures or both. In addition, the effects of a discrete cost structure are investigated, which has rarely been considered yet in literature. Furthermore, the cost difference between joint and successive working and spare capacity optimization is investigated. In the second part of the computational results, several heuristics for the network restoration problem are compared with respect to both solution quality and time.

Description: Mobile cellular communcication is a key technology in today's information age. Despite the continuing improvements in equipment design, interference is and will remain a limiting factor for the use of radio communication. This Ph. D. thesis investigates how to prevent interference to the largest possible extent when assigning the available frequencies to the base stations of a GSM cellular network. The topic is addressed from two directions: first, new algorithms are presented to compute "good" frequency assignments fast; second, a novel approach, based on semidef inite programming, is employed to provide lower bounds for the amount of unavoidable interference. The new methods proposed for automatic frequency planning are compared in terms of running times and effectiveness in computational experiments, where the planning instances are taken from practice. For most of the heuristics the running time behavior is adequate for inter active planning; at the same time, they provide reasonable assignments from a practical point of view (compared to the currently best known, but substantially slower planning methods). In fact, several of these methods are successfully applied by the German GSM network operator E-Plus. The currently best lower bounds on the amount of unavoidable (co-channel) interference are obtained from solving semidefinite programs These programs arise as nonpolyhedral relaxation of a minimum /c-parti tion problem on complete graphs. The success of this approach is made plausible by revealing structural relations between the feasible set of the semidefinite program and a polytope associated with an integer linear programming formulation of the minimum ^-partition problem. Comparable relations are not known to hold for any polynomial time solvable polyhedral relaxation of the minimum ^-partition problem. The appli cation described is one of the first of semidefinite programming for large industrial problems in combinatorial optimization.