Best practice space optimisation for office buildings

Michael May
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Michael May: University of Applied Sciences (HTW) Berlin, Wilhelminenhofstr. 75A, USA

Corporate Real Estate Journal, 2016, vol. 5, issue 2, 154-170

Abstract: The energy efficiency of office buildings is a major concern in real estate and facility management (REM/FM); however, often great potential, which can be easily unlocked, lies in the efficient use of available space. Carbon emissions are largely attributed to buildings and the sustainability of buildings (spaces) is a focus of governments and the private sector. Space allocation is tedious work and a great challenge for REM/FM managers, having a considerable economic impact on the entire organisation. Unsatisfying manual allocation results are due to the tremendous complexity involved in space assignment. To date, there are no algorithms that can solve this kind of problem efficiently. Existing IT systems, such as CAFM/IWMS, CAD/BIM or ERP systems, do not provide automated procedures. They can cope with the problem only interactively with a large time and cost effort and are unable to provide close-to-optimal solutions; however, they may provide important initial data and are able to leverage the results. This paper presents a novel approach towards automating this assignment task. The procedure assigns organisational units to available spatial resources taking into account space standards and constraints such as intercommunication, spatial proximity and pre-occupation. Allocation variants are generated and evaluated automatically according to their achievable reduction in cost, time, number of necessary moves and/or communication traffic. The approach allows space utilisation to be improved drastically. A number of best practice examples underpin this hypothesis.

Keywords: space efficiency and optimisation; best practice space utilisation; quadratic assignment problem (QAP); shortest paths; sustainability; IWMS (search for similar items in EconPapers)
JEL-codes: R3 (search for similar items in EconPapers)
Date: 2016
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