Analysis of three mathematical models of the Staff Rostering Problem

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...

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Bibliographic Details
Published inJournal of scheduling Vol. 15; no. 1; pp. 23 - 38
Main Authors Naudin, É., Chan, P. Y. C., Hiroux, M., Zemmouri, T., Weil, G.
Format Journal Article
LanguageEnglish
Published Boston Springer US 01.02.2012
Springer Nature B.V
Subjects
Algorithms
Artificial Intelligence
Business and Management
Calculus of Variations and Optimal Control; Optimization
Costs
Decomposition
Economics
Employees
Inequalities
Linear programming
Mathematical models
Operations Research/Decision Theory
Optimization
Scheduling
Searching
Staff
Studies
Supply Chain Management
Linear programming
Column generation
Rostering problem
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Summary: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.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1094-6136
1099-1425
DOI:10.1007/s10951-009-0155-3