|Title:||Days-off planning in large-scale multi-skill staff rostering|
|Authors :||Klinkert, Andreas|
|Conference details:||ECCO XXIV - The 24th Conference of the European Chapter on Combinatorial Optimization, Amsterdam, Netherlands, 2011|
|License (according to publishing contract) :||Not specified|
|Type of review:||Peer review (Abstract)|
|Subjects :||Integer programming; Rostering; Large scale|
|Subject (DDC) :||500: Natural sciences and mathematics |
658.4: Executive Management
|Abstract:||Staff scheduling and rostering typically involves a number of hierarchical subproblems including demand modeling, shift design, days-off scheduling, and staff assignment. When solving highly constrained large-scale rostering problems it is usually not computationally practical to deal simultaneously with all these tasks, and decomposing the problem into several separate modules is typical for real-world solutions. The problem considered here focuses on the days-off scheduling phase of the rostering process, and has been tackled in the context of an industrial project in the airport ground handling business. The main concern in days-off scheduling is to determine the off-work days for each staff member over the rostering planning horizon. In general, there are two categories of constraints to be considered. The first type is related to the individual line of work of each employee and originates from industrial regulations, labor contract, workplace agreements and individual preferences. The second type of constraints refers to the different days of the planning horizon and is concerned with satisfying the required daily staffing levels for each shift. According to the setting in our project, we assume that the required shifts and their staffing levels for each day have been determined prior to the days-off scheduling phase. Furthermore we assume a multi-skill staff environment where shifts can only be assigned to employees with appropriate skills. An integer programming model has been developed which is able to solve the complex large-scale problems posed by the industrial project partner. The Gurobi 4 solver generates high quality solutions within a few hours which clearly outperform the sophisticated solutions constructed manually by the experts at the planning department of the ground handling company.|
|Departement:||School of Engineering|
|Organisational Unit:||Institute of Data Analysis and Process Design (IDP)|
|Publication type:||Conference Other|
|Appears in Collections:||Publikationen School of Engineering|
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