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Was ist binare optionen trading Integer Reformulations of Robust b-Matching Problems - Using Few Integer Variables In the talk we consider robust two-stage bipartite b-matching problems with one or several knapsack constraints that link the first stage solution to the second stage solution.

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In ATM an efficient planning of runway utilization is one of the main challenges. Thereby, uncertainty and inaccuracy often lead to deviations from the actual plan or schedule. By using ideas from robust optimization this uncertainty can be incorporated into the initial computation of the plans.

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More precisely, each aircraft needs to be assigned to a time slot at the first stage before the uncertainty reveals. If an uncertain scenario occurs the plan might become infeasible and the aircraft need to be replanned in the second binare exponentiation mips.

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To this end, second stage solutions are desired, that do not differ too much from the first stage plan. The restriction of the replanning action may be modeled by one or several special knapsack constraints.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Abstract This paper deals binare exponentiation mips an optimization problem encountered in the field of transport of goods and services, namely the K-traveling repairman problem K-TRP. This problem is a generalization of the metric traveling repairman problem TRP which is also known as the deliveryman problem and the minimum latency problem.

A straight forward way is to formulate the resulting two-stage bipartite b-matching problem with one or several knapsack constraints as a binary binare exponentiation mips integer program IP.

Following the idea of Bader et al.

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To preserve integrality, an appropriate so called affine TU decomposition of the constraint matrix needs to be found. For the two-stage bipartite b-matching problem with several knapsack constraints an appropriate affine TU decomposition cannot be derived in a straight forward way.

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We give a similar decomposition of the constraint matrix and prove that this decomposition preserves integrality and thus allows a MIP reformulation with less integer variables. In a computational study we show that binare exponentiation mips compared to solving the IP formulation that only uses binary variables, root bounds and cpu times can significantly be improved, when the reformulated MIPs are solved.

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Moreover, several instances could only be solved when the MIP reformulations are used. Preprint,