A branch-and-price algorithm for the multi-activity multi-task shift scheduling problem

The multi-activity multi-task shift scheduling problem consists in assigning interruptible activities and uninterruptible tasks to a set of employees in order to satisfy a demand function. In this paper, we consider the personalized variant of the problem where the employees have different qualifications, preferences, and availabilities. We present a branch-and-price algorithm to solve this problem. The pricing subproblems in column generation are formulated with context-free grammars that are able to model complex rules in the construction of feasible shifts for an employee. We present results for a large set of instances inspired by real cases and show that this approach is sufficiently flexible to handle different classes of problems.