R. Beier

Publications18
h-index11
Citations497
Highly Influential Citations43
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Random knapsack in expected polynomial time
TLDR
We prove, for various input distributions, that the number of dominating solutions (i.e., Pareto-optimal knapsack fillings) to this problem is polynomially bounded in number of available items. Expand
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Typical properties of winners and losers in discrete optimization
TLDR
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e. Expand
  • 72
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Smoothed Analysis of Three Combinatorial Problems
TLDR
We study the smoothed complexity of three classical discrete problems: quicksort, left-to-right maxima counting and shortest paths. Expand
  • 55
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Typical Properties of Winners and Losers in Discrete Optimization
TLDR
We present a probabilistic analysis of a large class of combinatorial optimization problems containing all binary optimization problems defined by linear constraints and a linear objective function over $\{0,1\}^n$. Expand
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A powerful heuristic for telephone gossiping
TLDR
A refined heuristic for computing schedules for gossiping in the telephone model is presented. Expand
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Computing equilibria for congestion games with (im)perfect information
TLDR
We study algorithmic questions concerning a basic microeconomic congestion game in which there is a single provider that offers a service to a set of potential customers. Expand
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Probabilistic analysis of knapsack core algorithms
TLDR
We study the average-case performance of algorithms for the binary knapsack problem. Expand
  • 22
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The Knapsack Problem
TLDR
An algorithm for solving a classic optimization problem – how best to pack a knapsack for hike, taking into account the weight and the associated profit of each object carried. Expand
  • 3
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The Smoothed Number of Pareto Optimal Solutions in Bicriteria Integer Optimization
TLDR
A well established heuristic approach for solving various bicriteria optimization problems is to enumerate the set of Pareto optimal solutions, typically using some kind of dynamic programming approach. Expand
  • 39
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Random knapsack in expected polynomial time
TLDR
We present the first average-case analysis proving a polynomial upper bound on the expected running time of an exact algorithm for the 0/1 knapsack problem. Expand
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