A Decision Support System for Multi-Criteria Assessment of Large Building Stocks

Abstract

Both public administrations and private owners of large building stocks need to work out plans for the management of their property, while having to deal with yearly budget limitations. Particularly for the former, this is a rather critical challenge, since public administrations are given the responsibility of sticking to very strict budget distributions over the years. As a consequence, when planning the actions to be taken on their building stocks in order to comply with their current use and the legislation in-force, they need to classify refurbishment priorities. The aim of this paper is to develop a first tool based on Bayesian Networks that offers an effective decision support service for owners even in case some information is incomplete. This tool can be used to evaluate the compliance of existing buildings with the latest standards. The decision support platform proposed includes a multi-criteria evaluation approach combining several performance indicators, each of which related to a specific regulatory area. This tool can be applied to existing buildings, where the building with the lowest score shows the highest priority of intervention. Also, the platform performs an assessment of expected costs for required refurbishment or renovation actions.

Ranking of Heritage Building Conversion Alternatives by Applying BIM and MCDM: A Case of Sapieha Palace in Vilnius

“…As BIM modeling is founded on development of a 3D parametric model that is gradually updated during different stages using various methods [16,19] and technologies [24,70], the process of creating a 3D model is described below.…”

“…Digitalization of the heritage buildings is influenced by several properties such as [70,71]: There is no final solution for how to model the objects of built heritage. An issue of 3D modelling cannot be always resolved by using a single technique.…”

Identifying optimal renovation schedules for building portfolios: Application in a social housing context under multi-year funding constraints

“…1.3.1 Building stock modelling Building stocks studied in previous articles are various in terms of size and type. The smallest building stocks consisted in two buildings [7,36], while some studies considered thousands of buildings [13,23,31,32,38]. Often 5 to 50 different buildings were considered [8][9][10][11]24,34,35,37].…”

“…Buildings were grouped in one district or one city, or they were spread over a large territory such as a region or a country. In most cases, buildings in a stock had the same use, and several types of stock were studied: housing stocks [6,8,13,23,30,32,35,37,38], stocks of schools or university buildings [9,24,36], or stocks of offices or commercial buildings [10,11,33,34].…”

“…Regarding the stock modelling, a bottom-up approach was adopted in all papers of Table 1. For small stocks, the engineering method was chosen and all buildings were fully described based on real buildings [7,10,30,34,36,37]. For larger stocks, when data was available, a set of representative buildings was sometimes selected using clustering methods or expert knowledge.…”