جستجوی مقالات مرتبط با کلیدواژه « Group Decision Analysis » در نشریات گروه « فنی و مهندسی »

In today's world, one of the most efficient ways to build large projects and infrastructure is related to public-private partnership (3P) projects. This method is based on the partnership between the public and private sectors and exempts the government from providing financial, human and equipment resources along with taking risks in the construction of the project. In this method, after construction and operation, the project is handed over to governments and made available to the public. In this article, following the removal of obstacles to production and development projects, we used 3P approach in the face of intuitive fuzzy uncertainty to bring management decisions closer to the outside world. Meanwhile, an integrated group decision analysis based on intuitionistic fuzzy utility degree method and intuitionistic fuzzy preference evaluation technique is tailored to compute the experts’ weights and criteria importance, respectively. Then, a novel ranking approach based on positive/negative ideal solutions and relative closeness coefficient under intuitionistic fuzzy set theory is proposed to solve the 3P urban development project selection problem. Finally, in order to evaluate the proposed method and determine its efficiency for use in large projects, a case study of urban development is used, and comparisons are made between previous methods and the proposed method.

– Sustainable evaluation of construction projects in strategy-focused condition is the main issue for municipalities to appropriately improve public sector services. In this respect, the group decision-making methods could help experts to select suitable sustainable projects and to schedule them regarding their ranking results. Therefore, the objective of this study is to present a hybrid group decision-making approach based on hesitant fuzzy sets theory to select the best strategic project for Tehran municipality. Hesitant fuzzy sets theory regarding the other modern fuzzy sets could assist the experts in assessing the candidate strategic projects based on evaluation criteria by assigning some membership degrees under a set to decrease the judgments’ errors in vague environments. In this proposed approach, the weight of each decision maker (DM) is determined according to the proposed hesitant fuzzy collective wisdom weighting (HFCWW) method. Besides, the evaluation criteria weights are determined based on the presented hesitant fuzzy preference weighting (HFPW) technique. Hence, hesitant fuzzy utility index method is defined to rank the candidate strategic projects. Finally, a real case study about the sustainable strategic project selection for Tehran municipality is provided to represent the feasibility and applicability of the proposed framework.

Selecting the most suitable optimal point among the Pareto optimal points could help the experts to make an appropriate decision in an uncertain and complex situation. In this paper, an evaluating and ranking approach is proposed based on hesitant fuzzy set environment to assess the obtained Pareto optimal points from the proposed bi-objective multi-echelon supply chain model with locating distribution centers. In this respect, the proposed model has elaborated for perishable products based on fuzzy customers' demand. To address the issue, the possibilistic chance constraint programming approach has manipulated based on the trapezoidal fuzzy membership function. Moreover, the proposed hesitant fuzzy ranking approach is constructed based on group decision analysis and the last aggregation approach. Thereby, the last aggregation approach by aggregating the experts' opinions in last step could prevent the data loss. However, a case study about the perishable dairy products is considered to indicate the applicability of the proposed bi-objective multi-echelon supply chain model with locating distribution centers. Finally, a comparative analysis is provided between the obtained results and the current practice to show the feasibility and efficiency of the proposed model.

In recent two decades, countries focused on extraction of the minimum amount of fossil fuels and utilization of the renewable energies based on their policies and environmental considerations. Thus, choosing the best renewable energy alternative plays a significant role on the investments. Among the classical decision approaches used in the literature, a hesitant fuzzy sets (HFSs) theory is an appropriate tool to deal with uncertain and imprecise conditions. The HFSs can help the decision makers or experts in an energy sector to consider some membership degrees for a renewable energy alternative regarding to the conflicted criteria under a set. The aim of this paper is to propose a hierarchical complex proportional assessment (COPRAS) method to consider subjective judgments and objective opinions based on the HFS theory for multi-criteria group decision making (MCGDM) problems. In addition, the hesitant fuzzy decision matrix and main criteria along with sub-criteria are defined based on linguistic variables and then are converted to hesitant fuzzy elements. In the proposed approach, weights of experts are different and computed by a proposed hesitant fuzzy entropy method. Also, the weights of main criteria are determined by a new relation in n levels of the hierarchy structure with experts'' risk preferences. Finally, a real case study in Iran on the renewable energy selection in the hierarchy structure is presented and a hesitant fuzzy hierarchical complex proportional assessment (HF-HCOPRAS) method is applied in order to show the applicability of the proposed approach.