The Steiner cycle and path cover problem on interval graphs

The Steiner path problem is a common generalization of the Steiner tree and the Hamiltonian path problem, in which we have to decide if for a given graph there exists a path visiting a fixed set of terminals. In the Steiner cycle problem we look for a cycle visiting all terminals instead of a path. The Steiner path cover problem is an optimization variant of the Steiner path problem generalizing the path cover problem, in which one has to cover all terminals with a minimum number of paths. We study those problems for the special class of interval graphs. We present linear time algorithms for both the Steiner path cover problem and the Steiner cycle problem on interval graphs given as endpoint sorted lists. The main contribution is a lemma showing that backward steps to non-Steiner intervals are never necessary. Furthermore, we show how to integrate this modification to the deferred-query technique of Chang et al. to obtain the linear running times.

     

Intermediaries in the relevance-gap debate: A systematic review of consulting roles

A highly contested issue in management science is its relevance to practice. Despite third parties’ potentially significant role in changing the interaction between divided parties, the long-standing literature on the relevance gap has paid third parties little systematic attention. Drawing on a boundary-spanning perspective, and the concept of brokerage in particular, we review how the consultant role is discussed as an intermediary third party between management science and management practice. Based on a systematic literature review of 133 articles, we identify different intermediary consultant roles linking management science to management practice. Our findings detail how the practices associated with intermediary consultant roles performed by academics or practitioners relate to several key relevance criteria, how management knowledge flows when including intermediaries and how intermediaries in different roles relate to different audiences. Based on the findings, we develop a third-party model of intermediary consultant roles and knowledge flows. The model indicates the theoretical significance of third parties in shaping the interaction and knowledge flows between management science and management practice and has theoretical implications for understanding the persistence of the relevance gap. Regarding practical implications, we suggest how management scientists could target third parties as new key practitioner audiences. Considering third parties, and thus moving away from a two-party view, opens up promising directions for further research on the roles and role shifts of various intermediary actors and on how different intermediary audiences may appreciate different types of academic knowledge.     

Optimal Steiner trees under node and edge privacy conflicts

Journal of Combinatorial Optimization - In this work, we suggest concepts and solution methodologies for a series of strategic network design problems that find application in highly data-sensitive...     

The Determinants and Some Consequences of Unemployed Workers' Wage Demands

This paper studies the determinants and consequences in the early stages of the hiring process of unemployed workers' wage demands using direct data on workers' wage requests. We show that most unemployed workers want a wage close to their previous wage, and thus much more than they get in unemployment benefits. However, some groups, such as women, tend to demand lower wages. Moreover, we find that workers with high wage demands are contacted by firms less often than otherwise similar workers with lower wage demands. Thus, our results suggest that too high wage demands may contribute to high unemployment.     

An approximation algorithm for a general class of parametric optimization problems

Journal of Combinatorial Optimization - In a (linear) parametric optimization problem, the objective value of each feasible solution is an affine function of a real-valued parameter and one is...