Usage of multicriteria decision-making support arsenal for strategic planning in environmental protection sphere

2017 ◽  
Vol 24 (5-6) ◽  
pp. 227-238 ◽  
Author(s):  
Vitaliy Tsyganok ◽  
Sergii Kadenko ◽  
Oleg Andriychuk ◽  
Pavlo Roik
2013 ◽  
Vol 2 (2) ◽  
pp. 143 ◽  
Author(s):  
Pawel Tadeusz Kazibudzki ◽  
Andrzej Z Grzybowski

Deriving true priority vectors from intuitive pairwise comparison matrices (PCMs) and consistency measurement of decision makers judgments about their genuine weights are crucial issues within the multicriteria decision making support methodology called Analytic Hierarchy Process (AHP). The most popular procedure in the ranking process, constitutes the Right Eigenvector Method (REV). The inventor of the AHP convinces that as long as inconsistent PCMs are allowed in the AHP none of the other existing procedures qualify and the REV provides the only right solution in this process. The objective of this scientific paper is to examine if the former opinion can be considered as experimentally confirmed. For this purpose it was decided to apply Monte Carlo methodology. However, rather than simulate and analyze simulations results for a single PCM, as it has been done so far by many other authors, we decided to design and analyze computer simulations results for a singular model of the AHP framework. Our findings lead to inevitable conclusion that the REV cannot longer be perceived as a dominant procedure within the AHP methodology, especially when nonreciprocal PCMs are considered. It was verified empirically in our research that in the situation when nonreciprocal PCMs are considered the REV impoverishes the entire AHP methodology by its lack of PCMs inconsistency measure in such cases. Moreover, it provides less accurate rankings for a particular decision in comparison to other presented methods. It was also unequivocally verified that the enforced reciprocity of PCM leads directly to worse estimates of priorities weights. Altogether, it seems very important from the perspective of methodology supporting multicriteria decision making, the crucial process embedded in most of management activity. In the consequence, because the REV recedes other prioritization procedures available for the AHP methodology, it is advised to consider them instead, especially under some circumstances of an important and very tight managerial decisions.


Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1334
Author(s):  
Katarina Rogulj ◽  
Jelena Kilić Kilić Pamuković ◽  
Majda Ivić

Problems in real life usually involve uncertain, inconsistent and incomplete information. An example of such problems is strategic decision making with respect to remediation planning of historic pedestrian bridges. The multiple decision makers and experts, as well as the various mutually conflicting criteria, unknown criteria weights, and vagueness and duality in final decisions, provide motivation to develop a methodology that is able to resist the challenges implicit in this problem. Therefore, the aim of this research was to propose an algorithm based on the theory of rough neutrosophic sets in order to solve the problem of strategic planning with respect to the remediation of historic pedestrian bridges. A new multicriteria decision-making model is developed that is a fusion of rough set and neutrosophic set theory. A new cross entropy is proposed under a rough neutrosophic environment that does not possess the shortcomings of asymmetrical character and unknown occurrences. Additionally, a weighted rough neutrosophic symmetric cross entropy is proposed. Furthermore, a rough neutrosophic VIKOR method is introduced, with which the values of the utility measure, regret measure and VIKOR index are obtained. These values, as well as the weighted rough neutrosophic symmetric cross entropy measure, are used to provide a ranking of historic pedestrian bridges favorable to remediation. Finally, an illustrative example of the strategic planning of remediation for historic pedestrian bridges is solved and compared to other research, demonstrating the robustness, feasibility and efficacy of the model when dealing with complex multicriteria decision-making processes.


SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110360
Author(s):  
Fengsheng Chien ◽  
Chia-Nan Wang ◽  
Ka Yin Chau ◽  
Van Thanh Nguyen ◽  
Viet Tinh Nguyen

The uses and management of capital is extremely important to the operation of any businesses. However, not all businesses have available capital, so the use of loans in many different forms is always an effective solution in managing corporate finance. Accompanying with businesses, many financial leasing companies have implemented products and programs to lend money to businesses with low interest rates. So, choosing the best financial leasing company is a primary concern of businesses. To increase competitiveness, financial leasing companies often offer preferential conditions to attract businesses. Choosing the best financial leasing service to leasing is important and necessary to those businesses. Thus, the selection of a financial leasing company by small and medium enterprises benefits from the application of Multicriteria Decision-Making (MCDM) methods which allows the decision maker to consider various qualitative and quantitative criteria. In this article, the author applied Fuzzy Analytical Network Process (FANP) to calculate the related criteria weights of the financial leasing company selection problem of businesses. Then, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank the potential decision-making units. This research establishes one complete and efficient model for financial leasing company selection using FANP and TOPSIS methods. The proposed model is then applied into a real-world case study to demonstrate its feasibility.


Author(s):  
Luisa Andrea González-Cruz ◽  
Luis Fernando Morales-Mendoza ◽  
Alberto Alfonso Aguilar-Lasserre ◽  
Catherine Azzaro-Pantel ◽  
Paulina Martínez-Isidro ◽  
...  

Author(s):  
Jian Li ◽  
Li-li Niu ◽  
Qiongxia Chen ◽  
Zhong-xing Wang

AbstractHesitant fuzzy preference relations (HFPRs) have been widely applied in multicriteria decision-making (MCDM) for their ability to efficiently express hesitant information. To address the situation where HFPRs are necessary, this paper develops several decision-making models integrating HFPRs with the best worst method (BWM). First, consistency measures from the perspectives of additive/multiplicative consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced. Second, several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs. The main characteristic of the constructed models is that they consider all the values included in the HFBWPRs and consider the same and different compromise limit constraints. Third, an absolute programming model is developed to obtain the decision-makers’ objective weights utilizing the information of optimal priority weight vectors and provides the calculation of decision-makers’ comprehensive weights. Finally, a framework of the MCDM procedure based on hesitant fuzzy BWM is introduced, and an illustrative example in conjunction with comparative analysis is provided to demonstrate the feasibility and efficiency of the proposed models.


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