Search

Millions of employees around the world work in irregular rosters. The quality of these rosters is of utmost importance. High-quality rosters should be attractive on an individual level, but also divide the work fairly over the employees. We develop novel methodology to compute the trade-off between fairness and attractiveness in crew rostering. First, we propose an intuitive fairness scheme for crew rostering and analyze its theoretical performance. To do so, we introduce the approximate resource-allocation problem. This extension of the resource-allocation problem provides a framework for analyzing decision making in contexts where one relies on approximations of the utility functions. Fairness is a typical example of such a context due to its inherently subjective nature. We show that the scheme has "optimal" properties for a large class of approximate utility functions. Furthermore, we provide a tight bound on the utility loss for this scheme. We then present a unified approach to crew rostering. This approach integrates our proposed fairness scheme with a novel mathematical formulation for crew rostering. We call the resulting problem the Fairness-Oriented Crew Rostering Problem and develop a dedicated exact Branch-Price-and-Cut solution method. We conclude by applying our solution approach to practical instances from Netherlands Railways, the largest passenger railway operator in the Netherlands. Our computational results confirm the importance of taking the fairness–attractiveness trade-off into account. This paper was accepted by Yinyu Ye, optimization. [ABSTRACT FROM AUTHOR]

In most policy analysis studies there are a large number of alternative policies and a large number of impacts to be considered. Time and budget constraints make it impossible to calculate all the impacts for all of the alternatives. As a result, such studies include some process for reducing the number of alternatives to be examined in detail. The process is often implicit and nonscientific (e.g., only the decisionmaker's three favorite alternatives are considered). This paper suggests that policy analysis studies explicitly include a screening step, in which the alternatives to be examined in detail and those to be excluded from further consideration are chosen in a scientific and systematic manner. The output from this step is a relatively small set of policy alternatives that are sufficiently attractive that they deserve a more thorough evaluation. Two general screening strategies are described. They are illustrated by describing the screening step in a study to help determine an overall water management policy for the Netherlands. [ABSTRACT FROM AUTHOR]