Consider an important meeting to be held in a team-based organization. Taking availability constraints into account, an online scheduling poll is being used in order to decide upon the exact time of the meeting. Decisions are to be taken during the meeting, therefore each team would like to maximize its relative attendance (i.e. the proportional number of its team members attending the meeting). We introduce a corresponding game, where each team can declare a lower total availability in the scheduling poll in order to improve its relative attendance—the pay-off. We are especially interested in situations where teams can form coalitions. We provide an efficient algorithm that, given a coalition, finds an optimal way for each team in a coalition to improve its pay-off. In contrast, we show that deciding whether such a coalition exists is NP-hard. We also study the existence of Nash equilibria: Finding Nash equilibria for various small sizes of teams and coalitions can be done in polynomial time while it is coNP-hard if the coalition size is unbounded.

We study the (parameterized) complexity of Shift Bribery for multiwinner voting rules. We focus on the SNTV, Bloc, k-Borda, and Chamberlin-Courant rules, as well as on approximate variants of the Chamberlin-Courant rule, since the original rule is NP-hard to compute. We show that Shift Bribery tends to be significantly harder in the multiwinner setting than in the single-winner one by showing settings where Shift Bribery is easy in the single-winner cases, but is hard (and hard to approximate) in the multiwinner ones. We show that the non-monotonicity of those rules which are based on approximation algorithms for the Chamberlin--Courant rule sometimes affects the complexity of Shift Bribery.

We extend work by Christian et al. [Review of Economic Design 2007] on lobbying in multiple referenda by first providing a more fine-grained analysis of the computational complexity of the NP-complete Lobbying problem. Herein, given a binary matrix, the columns represent issues to vote on and the rows correspond to voters making a binary vote on each issue. An issue is approved if a majority of votes has a 1 in the corresponding column. The goal is to get all issues approved by modifying a minimum number of rows to all-1-rows. In our multivariate complexity analysis, we present a more holistic view on the nature of the computational complexity of Lobbying, providing both (parameterized) tractability and intractability results, depending on various problem parameterizations to be adopted. Moreover, we show non-existence results concerning efficient and effective preprocessing for Lobbying and introduce natural variants such as Restricted Lobbying and Partial Lobbying.

Network management is a complex task involving various challenges, such as the heterogeneity of the infrastructure or the information flood caused by billions of log messages from different systems and operated by different organiza- tional units. All of these messages and systems may contain information relevant to other operational units. For example, in order to ensure reliable DSL connections for IPTV cus- tomers, optimal customer traffic path assignments for the current network state and traffic demands need to be evalu- ated. Currently reassignments are only manually performed during routine maintenance or as a response to reported problems. In this paper we present a decision support sys- tem for this task. In addition, the system predicts future pos- sible demands and allows reconfigurations of a DSL access network before congestions may occur.