Analysis of three mathematical models of the Staff Rostering Problem

Authors:
É. Naudin;P. Y. Chan;M. Hiroux;T. Zemmouri;G. Weil
Affiliations:
Equitime, Gières, France 38610 and Eurodecision, Versailles, France 78000;Equitime, Gières, France 38610;Equitime, Gières, France 38610;Equitime, Gières, France 38610;Equitime, Gières, France 38610
Venue:
Journal of Scheduling
Year:
2012

Citing 4
Cited 1

A Hybrid Tabu Search Algorithm for the Nurse Rostering Problem

SEAL'98 Selected papers from the Second Asia-Pacific Conference on Simulated Evolution and Learning on Simulated Evolution and Learning
Branch-And-Price: Column Generation for Solving Huge Integer Programs

Operations Research
A Column Generation Approach for Large-Scale Aircrew Rostering Problems

Operations Research
The State of the Art of Nurse Rostering

Journal of Scheduling

Alternative MIP formulations for an integrated shift scheduling and task assignment problem

Discrete Applied Mathematics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Staff rostering is a major challenge in the service sector, where exploitation costs are essentially made up of staffing costs. Searching for an optimum has direct economic returns but the rosters must satisfy numerous legal constraints. This paper presents work on an exact approach using branch-and-price methods on a concrete situation. We develop three MILP models and extend them with valid inequalities to two cases. Their computation results on a set of 960 tests covering several scenarios will then be compared and analyzed.