Publication type: Conference other
Type of review: Peer review (abstract)
Title: Workforce planning in airport logistics : a real-world business application
Authors : Klinkert, Andreas
et. al : No
Proceedings: CMS-MMEI-2019 : collection of abstracts
Conference details: 16th Conference on Computational Management Science (CMS 2019), Chemnitz, Germany, 27-29 March 2019
Issue Date: 28-Mar-2019
Publisher / Ed. Institution : European Working Group on Stochastic Programming and Applications
Language : English
Subjects : Rostering; Large-scale; Staff scheduling
Subject (DDC) : 500: Natural sciences and mathematics
658.3: Human resource management
Abstract: Staff scheduling and rostering involves a number of hierarchical subproblems including demand modeling, task generation, shift design, days-off scheduling, shift assignment and real-time dispatching. When solving highly constrained large-scale workforce planning problems it is usually not computationally practical to deal simultaneously with all these tasks. Real-world software solutions typically decompose the overall planning task into heuristically designed subproblems which then are tackled by a variety of suitable exact and heuristic methods. We present results from a major research and business project with Swissport International Ltd., the largest ground handling company worldwide, which provides services for 850 client companies and 265 million passengers a year, with a workforce of 68 000 personnel at 315 airports. During a long-term strategic cooperation, a high-performance software for automated staff scheduling in airport logistics has been developed, which is able to solve the complex large-scale rostering problems in Swissports airport operations. The solution methodology comprises a broad range of optimization techniques including preprocessing, decomposition and relaxation approaches, mixed-integer programming models, and various heuristic procedures. We start with an introduction to the business environment of the project and show its actual planning context which comprises other software tools and human planning activities related to the workforce scheduling process. We provide insight into several aspects of the solution process, including the analysis and preprocessing phase which turned out to be crucial for the entire planning system. We provide further insight into decomposition strategies, mathematical problem structure, and algorithmic approaches. Finally, we present computational experience with real world instances and discuss operational impacts of the developed planning tool. Bottom line benefits include faster and more robust planning processes, improved roster quality, better fairness, reduced planning capacity requirements, and as a result, substantial financial savings.
Fulltext version : Published version
License (according to publishing contract) : Not specified
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Appears in Collections:Publikationen School of Engineering

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