7 research outputs found
Type-2 neutrosophic number based multi-attributive border approximation area comparison (MABAC) approach for offshore wind farm site selection in USA.
The technical, logistical, and ecological challenges associated with offshore wind development necessitate an extensive site selection analysis. Technical parameters such as wind resource, logistical concerns such as distance to shore, and ecological considerations such as fisheries all must be evaluated and weighted, in many cases with incomplete or uncertain data. Making such a critical decision with severe potential economic and ecologic consequences requires a strong decision-making approach to ultimately guide the site selection process. This paper proposes a type-2 neutrosophic number (T2NN) fuzzy based multi-criteria decision-making (MCDM) model for offshore wind farm (OWF) site selection. This approach combines the advantages of neutrosophic numbers sets, which can utilize uncertain and incomplete information, with a multi-attributive border approximation area comparison that provides formulation flexibility and easy calculation. Further, this study develops and integrates a techno-economic model for OWFs in the decision-making. A case study is performed to evaluate and rank five proposed OWF sites off the coast of New Jersey. To validate the proposed model, a comparison against three alternative T2NN fuzzy based models is performed. It is demonstrated that the implemented model yields the same ranking order as the alternative approaches. Sensitivity analysis reveals that changing criteria weightings does not affect the ranking order
Assessment of the agriculture supply chain risks for investments of agricultural small and mediumsized enterprises (SMEs) using the decision support model
A key challenge in responding to the emerging challenges in agri-food
supply chains is encouraging continued new investment. This is related
to the recognition that agricultural production is often a lengthy process
requiring ongoing investments that may not produce expected
returns for a prolonged period, thereby being highly sensitive tomarket
risks. Agricultural productions are generally susceptible to different serious
risks such as crop diseases, weather conditions, and pest infections.
Many practitioners in this domain, particularly small and medium-sized
enterprises (SMEs), have shifted toward digitalization to address such
problems. To help with this situation, the current paper develops an
integrated decision-making framework, with the Pythagorean fuzzy
sets (PFSs), the method for removal effects of criteria (MEREC), the ranksum
(RS) and the gained and Lost dominance score (GLDS) termed as
PF-MEREC-RS-GLDS approach. In this approach, the PF-MEREC-RS
method is applied to compute the subjective and objective weights of
the main risks to assess the agriculture supply chain for investments of
SMEs, and the PF-GLDS model is used to assess the preferences of
enterprises over different the main risks to assess of the agriculture supply
chain for investments of SMEs. An empirical case study is taken to
evaluate the main risks to assess the agriculture supply chain for SME
investments. Also, comparison and sensitivity investigation are made to
show the superiority of the developed framework
Single-valued neutrosophic TODIM method based on cumulative prospect theory for multi-attribute group decision making and its application to medical emergency management evaluation
In recent years, emergent public health events happen from time
to time, which puts forward new requirements for the establishment of a perfect medical emergency system. It is a new direction
to evaluate the effectiveness of medical emergency systems from
the perspective of multi-attribute group decision making
(MAGDM) issues. In such article, we tend to resolve the MAGDM
issues under single-valued neutrosophic sets (SVNSs) with TODIM
method based on cumulative prospect theory (CPT). And the single-valued neutrosophic TODIM method based on CPT (CPT-SVNTODIM) for MAGDM issues are developed. This new method not
only inherits advantages of classical TODIM method, but also has
further improvement in some aspects. For example, we set up the
entropy to calculate attribute weights for ensuring the more
objective decision-making process. Furthermore, it is also an
extension of MAGDM method to utilize single-valued neutrosophic numbers (SVNNs) to depict decision makers’ ideas. In addition, we introduce the application of CPT-SVN-TODIM method in
the assessment of medical emergency management. And finally,
the reliability of CPT-SVN-TODIM method is confirmed by comparing with some other methods
Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding
Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management