In the age of Big Data, efficient algorithms are now in higher demand more than ever before.
While Big Data takes us into the asymptotic world envisioned by our pioneers, it also …

On-demand resource provisioning in cloud computing provides tailor-made resource
packages (typically in the form of VMs) to meet users' demands. Public clouds nowadays …

We give the first black-box reduction from approximation algorithms to truthful approximation
mechanisms for a non-trivial class of multi-parameter problems. Specifically, we prove that …

Suppose we want to drive from New York to Boston. We care about the travel time, the total
distance, the simplicity of the route (eg number of turns), etc. Which route should we …

Viele Algorithmen sind in der Praxis effizient, obwohl ihre Laufzeit im Worst Case sehr
schlecht ist. Der Grund für diese Diskrepanz ist, dass die reine Betrachtung des Worst Case …

We present several new results about smoothed analysis of multiobjective optimization
problems. Motivated by the discrepancy between worst-case analysis and practical …

In this paper, we consider two-player zero-sum stochastic mean payoff games with perfect
information modeled by a digraph with black, white, and random vertices. These BWR …

A well-established heuristic approach for solving bicriteria optimization problems is to
enumerate the set of Pareto-optimal solutions. The heuristics following this principle are …

Euclidean optimization problems such as TSP and minimum-length matching admit fast
partitioning algorithms that compute near-optimal solutions on typical instances. In order to …

Consider an optimization problem with n binary variables and d+ 1 linear objective
functions. Each valid solution x∈{0, 1} n gives rise to an objective vector in Rd+ 1, and one …