Rolf H. Möhring

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We consider the problem to minimize the total weighted completion time of a set of jobs with individual release dates which have to be scheduled on identical parallel machines. Job processing times are not known in advance, they are realized on-line according to given probability distributions. The aim is to find a scheduling policy that minimizes the(More)
This paper deals with methods for solving resource-constrained project-scheduling problems. Among the project activities there can be resource conflicts due to the finite capacity of the resources. The paper aims at describing a new method for minimizing the expected makespan while all the possible resource conflicts get eliminated. The novelty of the(More)
We present a number of improvements of the basic variant of the arc-flag acceleration (Lauther, 1997, 2004) for point-to-point (P2P) shortest path computations on large graphs. Arc-flags are a modification to the standard Dijkstra algorithm and are used to avoid exploring unnecessary paths during shortest path computation. We assume that for the same input(More)
In many scheduling applications it is required that the processing of some job be postponed until some other job, which can be chosen from a pregiven set of alternatives, has been completed. The traditional concept of precedence constraints fails to model such restrictions. Therefore, the concept has been generalized to so-called and/or precedence(More)
PREFACE After having received my diploma from the Technische Universität Berlin in 1996, Rolf Möhring, the supervisor of my diploma thesis, offered me a research position in his group. At that time I was employed at a Berlin software company the head of which, Gert Scheschonk, strongly encouraged me to accept the offer. I accepted and in 1997 I began to(More)
We study an acceleration method for point-to-point shortest-path computations in large and sparse directed graphs with given nonnegative arc weights. The acceleration method is called the <i>arc-flag approach</i> and is based on Dijkstra's algorithm. In the arc-flag approach, we allow a preprocessing of the network data to generate additional information,(More)
We introduce a class of finite strategic games with the property that every deviation of a coalition of players that is profitable to each of its members strictly decreases the lexicographical order of a certain function defined on the set of strategy profiles. We call this property the Lexicographical Improvement Property (LIP) and show that it implies the(More)