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Multi-level departments-to-offices assignment with different room types

•Introduces the multi-level departments-to-offices assignment problem.•Proposes a multi-objective quadratic mathematical model formulation.•Presents a new heuristic approach with an innovative filtering procedure.•Analysis of heuristic with a large set of publicly available test instances.•Insights...

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Bibliographic Details
Published in:Computers & operations research 2019-10, Vol.110, p.60-76
Main Authors: Becker, Tristan, Zajac, Sandra, Steenweg, Pia Mareike, Imhoff, Lisa, Block, Julia Sophie
Format: Article
Language:English
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Summary:•Introduces the multi-level departments-to-offices assignment problem.•Proposes a multi-objective quadratic mathematical model formulation.•Presents a new heuristic approach with an innovative filtering procedure.•Analysis of heuristic with a large set of publicly available test instances.•Insights into the problem structure gained from a realistic case study. When a company moves to a new building, each department has to receive the room capacities it requires. Construction of large office buildings can take multiple years while organizational structures are subject to frequent change. At the time of building design, often only a rough capacity planning is carried out. An explicit assignment of departments to rooms is postponed until the building is almost finished. In addition to hard constraints with regard to the required number and type of rooms each department needs, various preferences have to be considered for an efficient level and room assignment. To support intra- and interdepartmental interactions, we consider the distances between the assigned rooms of each department and the proximity of related departments. Additionally, preferences with respect to the spatial location in the building are taken into account. We propose a new non-linear mathematical programming formulation for the multi-level departments-to-offices assignment problem with different room types. Standard solvers cannot produce relevant solutions from a practical perspective in an acceptable time. To solve a realistic problem, an innovative heuristic approach is proposed. Computational results across a large set of test instances demonstrate the general applicability of our approach. Finally, results and trade-offs between the different objectives are discussed extensively in a case study.
ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2019.05.015