Tunnel Boring Machine (TBM) selection using fuzzy multicriteria decision making methods

• Published in: Tunnelling and underground space technology 2012-07, Vol.30, p.194-204
• Main Authors: Yazdani-Chamzini, Abdolreza, Yakhchali, Siamak Haji
• Format: Article
• Language: English
• Subjects: Applied sciences; Boring machines; Buildings. Public works; Computation methods. Tables. Charts; Decision making; Exact sciences and technology; Fuzzy; Fuzzy AHP; Fuzzy logic; Fuzzy set theory; Fuzzy systems; Fuzzy TOPSIS; Mathematical models; MCDM; Structural analysis. Stresses; Tunnel Boring Machine (TBM); Tunnels (transportation); Tunnels, galleries
• ISSN: 0886-7798; 1878-4364
• DOI: 10.1016/j.tust.2012.02.021

► Selection type of TBM depends on the various parameters that some of these parameters are in conflicting with each other. ► TBM selection process is sophisticated and complex. ► AHP and TOPSIS methods are appropriate tools for selection under the complicated circumstances. ► Fuzzy approach is useful to handle the inherent uncertainty in decision making. ► Combining fuzzy AHP and fuzzy TOPSIS approaches is a new tool for making a decision under vague environmental. The problem of Tunnel Boring Machine (TBM) selection has a significant impact on the speed and cost of excavating sector; so that it is a strategic issue. On the other hand, selecting the optimum TBM among a pool of alternatives is a multicriteria decision making (MCDM) problem. In this paper, an evaluation model based on the fuzzy analytic hierarchy process (AHP) and another fuzzy MCDM technique, namely fuzzy technique for order performance by similarity to ideal solution (TOPSIS) is developed to help the tunneling designers in the process of the TBM selection under fuzzy environment where the vagueness and uncertainty are taken into account with linguistic variables parameterized by triangular fuzzy numbers. The fuzzy AHP is applied to form the structure of the TBM selection problem and to determine weights of the evaluation criteria, and fuzzy TOPSIS method is utilized to acquire final ranking. A real world case study is illustrated in order to demonstrate the potential of the proposed model for the TBM selection issue. It demonstrates the effectiveness and capability of the proposed model.