Implementation of Adjusted Fuzzy AHP Method in the Assessment for Reuse of Industrial Buildings

Abstract

With rapid economic development and restructuring, the number of old or obsolete buildings is growing in large cities. Construction practice has actively focused in recent decades on the regeneration of brownfield areas and creating opportunities for their cost-effective and sustainable reuse. Some of the buildings could be identified as-built industrial heritage whose purpose could be modified and used differently. Adaptive reuse can make a major contribution to sustainable development by reducing construction waste and saving natural resources. In the reuse management process, the problem is how to deal with multiple criteria that are imposed as factors in assessing the reuse of a building. Using the adjusted fuzzy analytical hierarchy process (FAHP), we explore the potential for the adaptation and new use of industrial buildings in the former area of Electronic Industry Nis (EI Nis) in Serbia. The standard FAHP, in which we determine the weights of each sub-criterion based on the expert’s evaluation, we adjusted for use when no pairwise comparison of existing alternatives was available. Multiple criteria evaluation was performed by applying many criteria and sub-criteria, taking into account the different spatial and physical performance of buildings, as well as their locational indicators. A case study is used to demonstrate the application of the method and show its effectiveness.

Fuzzy and Interval AHP Approaches in Sustainable Management for the Architectural Heritage in Smart Cities

“…The fuzzy AHP method is an extension of the crisp AHP method, where estimates are presented with fuzzy values [143]. Many researchers express a lot of methods and applications of the fuzzy AHP method [144][145][146]. These methods are used to find the preference weightings of indicators by subjective assessment [147,148].…”

Neutrosophic Completion Technique for Incomplete Higher-Order AHP Comparison Matrices

“…Figure 1 presents the triangular neutrosophic truth: indeterminacy and falsehood membership functions associated to the criteria weights. Additionally, Figure 1 shows the scalar weights that result after applying the deneutrosophication technique presented in Equations ( 21) and (22). 1 presents the triangular neutrosophic truth: indeterminacy and falsehood membership functions associated to the criteria weights.…”

“…A continuous membership function is a defined value in the real unit interval. Thus defined, the fuzzy sets theory establishes a practical baseline for modeling the non-probabilistic uncertainties of human thinking and has been therefore widely applied in decision-making problems in recent years [22][23][24].…”

A Comparative Study of FAHP with Type-1 and Interval Type-2 Fuzzy Sets for ICT Implementation in Smart Cities

“…In this paper, triangular and trapezoidal fuzzy numbers have used. A trapezoidal and triangular fuzzy number can be respectively denoted as ã = l, m l , m r , u and b = (l, m, u) with the membership functions [10,11]…”