4.7 Article

Product-cost modelling approach for the development of a decision support system for optimal roofing material selection

Journal

EXPERT SYSTEMS WITH APPLICATIONS
Volume 39, Issue 8, Pages 6857-6871

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2012.01.010

Keywords

TOPSIS; Knowledge-based system; Decision support system; Roofing material selection; Energy efficient building; Product-cost modelling

Funding

  1. Built Environment Research Institute, University of Ulster, Northern Ireland

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Selection of optimal roofing materials is very important but it is a complex and onerous task as varieties of materials are available for housing roof construction. In order to select suitable materials, an extensive range of criteria would need to be considered. This paper presents the framework and the development of a knowledge-based decision support system for material selection implemented in roofing material selection domain, called 'Knowledge-based Decision Support system for roofing Material Selection and cost estimating' (KDSMS). It was developed to facilitate the selection of optimal materials for different roof sub elements. The system consists of a database and knowledge base that is equipped with an inference engine. The former is used to store different types of roofing materials with assigned attribute values. The later is used to hold qualitative and quantitative knowledge which were collected from domain experts and other technical literatures such as building regulations, price guide book and product catalogues. The proposed system employs the TOPSIS (Technique of ranking Preferences by Similarity to the Ideal Solution) multiple criteria decision making method to solve materials selection and optimisation problem. This study utilised the available roofing materials in the UK housing market in developing the system reported. The main contribution of the developed system is that it provides a tool for the architects, quantity surveyors or self house builder to select optimal materials from a wide array of possibilities for different roof sub elements and also to estimate the conceptual cost for the roof element in the early stage of building design. (C) 2012 Elsevier Ltd. All rights reserved.

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