Critical factors of the application of nanotechnology in construction industry by using ANP technique under fuzzy intuitionistic environment

AbstractNanotechnology plays a significant role in construction industry. The construction industry has been employed nanomaterials to improve the performance of construction components and the safety of the structure and to reduce the energy consuming and the cost of maintenance. In other words, nanotechnology has a substantial impact on the construction industry. Therefore, it is necessary to identify and evaluate the critical factors of the application of nanotechnology in construction in order to concentrate on the most critical factors. However, several techniques have been developed to prioritize the evaluation criteria. Analytical network process (ANP) technique, a branch of multi criteria decision making (MCDM) methods, is a powerful tool to rank a limited number of criteria. This technique takes into account both tangible and intangible criteria in the process of formulation of a decision making problem. This method is capable of handling all types of independence and dependence relationships. On...

[1]  Florentin Smarandache,et al.  New Operations over Interval Valued Intuitionistic Hesitant Fuzzy Set , 2014 .

[2]  Jhuma Sadhukhan,et al.  Sustainability indicators for industrial ovens and assessment using Fuzzy set theory and Monte Carlo simulation , 2017 .

[3]  Li Dengfeng,et al.  New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions , 2002, Pattern Recognit. Lett..

[4]  Haiyan Zhao,et al.  Decision-theoretic rough fuzzy set model and application , 2014, Inf. Sci..

[5]  Abdolreza Yazdani-Chamzini,et al.  Proposing a new methodology based on fuzzy logic for tunnelling risk assessment , 2014 .

[6]  George Gargov,et al.  Elements of intuitionistic fuzzy logic. Part I , 1998, Fuzzy Sets Syst..

[7]  Yuhua Qian,et al.  Multigranulation fuzzy rough set over two universes and its application to decision making , 2017, Knowl. Based Syst..

[8]  Edmundas Kazimieras Zavadskas,et al.  A new hybrid model for evaluating the working strategies: case study of construction company , 2012 .

[9]  Charalampos Saridakis,et al.  Examining the role of CSR skepticism using fuzzy-set qualitative comparative analysis , 2014 .

[10]  Zeshui Xu,et al.  Information fusion for intuitionistic fuzzy decision making: An overview , 2016, Information Fusion.

[11]  Mohamed Saafi,et al.  Nano- and Microtechnology , 2005 .

[12]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[13]  G. Silva,et al.  Green buying behavior and the theory of consumption values: A fuzzy-set approach ☆ , 2016 .

[14]  Huawen Liu,et al.  Multi-criteria decision-making methods based on intuitionistic fuzzy sets , 2007, Eur. J. Oper. Res..

[15]  Deng-Feng Li,et al.  Multiattribute decision making models and methods using intuitionistic fuzzy sets , 2005, J. Comput. Syst. Sci..

[16]  Ching-Hsue Cheng,et al.  Using intuitionistic fuzzy sets for fault-tree analysis on printed circuit board assembly , 2006, Microelectron. Reliab..

[17]  Lazim Abdullah,et al.  A new type-2 fuzzy set of linguistic variables for the fuzzy analytic hierarchy process , 2014, Expert Syst. Appl..

[18]  Thomas L. Saaty,et al.  Decision making for leaders , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[19]  Abdolreza Yazdani-Chamzini,et al.  An integrated fuzzy multi criteria group decision making model for handling equipment selection , 2014 .

[20]  Donald R. Baer,et al.  Enhancing coating functionality using nanoscience and nanotechnology , 2003 .

[21]  Edmundas Kazimieras Zavadskas,et al.  Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the performance evaluation of oil producing companies , 2014, Expert Syst. Appl..

[22]  Wenzhong Zhu,et al.  Application of nanotechnology in construction - current status and future potential , 2004 .

[23]  Lazim Abdullah,et al.  Sustainable energy planning decision using the intuitionistic fuzzy analytic hierarchy process: choosing energy technology in Malaysia , 2016 .

[24]  Mahdi Bashiri,et al.  Selecting optimum maintenance strategy by fuzzy interactive linear assignment method , 2011 .

[25]  Abdolreza Yazdani-Chamzini,et al.  Proposing a New Model for Waste Dump Site Selection: Case Study of Ayerma Phosphate Mine , 2014 .

[26]  Edmundas Kazimieras Zavadskas,et al.  Ranking the strategies of mining sector through anp and topsis in a swot framework , 2011 .

[27]  José Carlos Rodriguez Alcantud,et al.  A novel algorithm for fuzzy soft set based decision making from multiobserver input parameter data set , 2016, Inf. Fusion.

[28]  Plamen P. Angelov,et al.  Optimization in an intuitionistic fuzzy environment , 1997, Fuzzy Sets Syst..

[29]  Weihua Xu,et al.  Double-quantitative rough fuzzy set based decisions: A logical operations method , 2017, Inf. Sci..

[30]  Murat Kucukvar,et al.  Application of the TOPSIS and intuitionistic fuzzy set approaches for ranking the life cycle sustainability performance of alternative vehicle technologies , 2016 .

[31]  Zun-Quan Xia,et al.  Multicriteria fuzzy decision-making methods based on intuitionistic fuzzy sets , 2007, J. Comput. Syst. Sci..

[32]  Sarfaraz Hashemkhani Zolfani,et al.  Planning the priority of high tech industries based on SWARA-WASPAS methodology: The case of the nanotechnology industry in Iran , 2015 .

[33]  Janusz Kacprzyk,et al.  Entropy for intuitionistic fuzzy sets , 2001, Fuzzy Sets Syst..

[34]  Deng-Feng Li,et al.  A ratio ranking method of triangular intuitionistic fuzzy numbers and its application to MADM problems , 2010, Comput. Math. Appl..

[35]  Diyar Akay,et al.  A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method , 2009, Expert Syst. Appl..

[36]  Arpan Kumar Kar,et al.  A hybrid group decision support system for supplier selection using analytic hierarchy process, fuzzy set theory and neural network , 2015, J. Comput. Sci..