Project safety evaluation by a new soft computing approach-based last aggregation hesitant fuzzy complex proportional assessment in construction industry

H. Gitinavard, S.M. Mousavi, B. Vahdani, A. Siadat
2017 Scientia Iranica. International Journal of Science and Technology  
In recent years, the implementation of safety management has been increased in construction projects by institutions, and many companies have recognized environmental and social effects of injuries at project work systems. In this regard, a novel decision model is presented based on a new version of complex proportional assessment method with last aggregation under a hesitant fuzzy environment. The decision makers (DMs) assign their opinions by hesitant linguistic variables that are converted
more » ... hat are converted to the hesitant fuzzy elements. Also, the DMs' judgments are aggregated in last step of decision making to decrease information loss. Since weights of the DMs or professional safety experts and evaluation criteria are not equal in practice, a new version of hesitant fuzzy compromise solution method is proposed to compute these weights. In addition, the criteria weights are determined based on proposed hesitant fuzzy entropy method. A real case study in developing countries about the safety of construction projects is considered to indicate the suitability and applicability of the proposed new hesitant fuzzy decision model with last aggregation approach. In addition, an illustrative example is prepared to show that the proposed approach is suitable and reliable in larger size safety problems. (A. Siadat). been first introduced by Torra and Narukawa [27] and Torra [28] , which could assist DMs or professional safety experts to express their judgments by some membership degrees for a safety alternative under a set. The HFS theory is known as a powerful tool in the literature that has applicable in hesitant situations and conditions. In this regard, Farhadinia [29] as well as Yu et al. [30] expressed that the HFSs can be considered in practical situations and real applications of MCDM problems due to having a set of possible values for the membership; in addition, this extension of fuzzy sets theory ensures anonymity and privacy, and it prevents the psychic contagion of DMs. For instance, if two project safety experts express the same value, then the value will emerge only once, and this assessment can be described by hesitant fuzzy elements (HFEs) [30] . Wang et al. [31] mentioned that the HFSs are helpful in handling the MCDM problems and in expressing under imprecise situations where DMs hesitate between several values before assigning their preferences. Zhang et al. [32] explained that the HFSs have prepared an effective way in relating with decision-making problems when some membership values are possible for an object or criterion. Rodríguez et al. [33] provided an overview on theory of HFSs by goal of preparing an obvious perspective on different tools, trends, and concepts regarding to this extension of fuzzy sets theory. In this regard, numerous operations, such as union and intersection, were developed for hesitant fuzzy sets; Zheng and Liangzhong [34] have surveyed the properties and algebraic structures of these operations. However, because of powerful logic and sets, some authors utilized the HFSs to solve their decision problems under uncertainty. In this respect, Yan [35] used the multi-attribute decision making by hesitant fuzzy information to solve the risk of marketing problem. Yu et al. [36] proposed generalized hesitant fuzzy bonferroni mean, and discussed about the desirable of its properties in detail to solve the financial strategy planning in a Chinese enterprise. Xu and Zhang [37] focused on the deviation method to compute the criteria weights with incomplete information and presented a TOPSIS method to solve the energy policy selection problem. Liu and Rodríguez [38] proposed a fuzzy representation for comparative linguistic expressions based on hesitant fuzzy linguistic term sets, and this approach was applied to a TOPSIS model for solving the supplier selection problem. Liu [39] extended some aggregation operators for aggregating the hesitant fuzzy linguistic information, and then used them to develop some approaches to solve the electrical power system safety problem. Therefore, the HFSs could be regarded as a suitable tool for dealing with the available imprecise information in project safety decision-making problems. It is because of the practically of the HFSs and the focusing of the related literature as a powerful tool to address the uncertainties in complex decision-making problems In addition, the interval-valued hesitant fuzzy set, which was first introduced by Chen et al. [40] in terms of the HFSs could assist the DMs by considering some interval-values membership degrees for an element under a set to decrease of the errors. Accordingly, some authors have considered the intervalvalued hesitant fuzzy sets theory to solve the complex decision-making problems. In this case, Chen et al. [40] extended a group decision-making approach regarding to the interval-valued hesitant preference operations. Xu and Zhang [37] constructed an optimization model to compute the attributes weights based on the maximizing deviation method. Then, they developed the TOPSIS technique based on intervalvalued hesitant fuzzy situations to solve the decision-making problems. Farhadinia [41] developed two clustering algorithms by focusing on relationship between entropy, distance and similarity measures for the interval-valued hesitant fuzzy sets and HFSs. Li and Peng [42] presented some Hamacher operations regarding to interval-valued hesitant fuzzy sets and then developed a practical approach for the evaluation of the shale gas areas. Zhang and Xu [43] proposed an interval-valued-based programming model for group decision-making problems under hesitant fuzzy situations with incomplete preference over potential alternatives. Engineering, University of Tehran, Iran in 2015 and 2013, respectively. His main research interests include fuzzy sets theory, multi-criteria decision-making under uncertainty, supply chain management, and applied operations research. He has published several papers in reputable journals and international conference proceedings. , facility location and design, multi-criteria decision making, uncertain programming, artificial neural networks, meta-heuristics algorithms and operations research applications. He has published numerous papers and book chapters in the aforementioned areas. Ali Siadat is Professor at Laboratoire de Conception, Fabrication Commande, Arts et Métier Paris Tech, Centre de Metz in Metz, France. His current research interests include: computer aided manufacturing, modeling and optimization of manufacturing processes, decision making in manufacturing, inspection planning and operations research applications. He has published numerous papers and book chapters in the aforementioned fields.
doi:10.24200/sci.2017.4439 fatcat:5su7sc5djng2pntn2rub4z4x6u