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

Modified EDAS Method Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making with Interval-valued Intuitionistic Fuzzy Information

The Interval-valued intuitionistic fuzzy sets (IVIFSs) based on the intuitionistic fuzzy sets combines the classical decision method is in its research and application is attracting attention. After comparative analysis, there are multiple classical methods with IVIFSs information have been applied into many practical issues. In this paper, we extended the classical EDAS method based on cumulative prospect theory (CPT) considering the decision makers (DMs) psychological factor under IVIFSs. Taking the fuzzy and uncertain character of the IVIFSs and the psychological preference into consideration, the original EDAS method based on the CPT under IVIFSs (IVIF-CPT-MABAC) method is built for MAGDM issues. Meanwhile, information entropy method is used to evaluate the attribute weight. Finally, a numerical example for project selection of green technology venture capital has been given and some comparisons is used to illustrate advantages of IVIF-CPT-MABAC method and some comparison analysis and sensitivity analysis are applied to prove this new methods effectiveness and stability.Comment: 48 page

SELECTION OF FORKLIFT UNIT FOR TRANSPORT HANDLING USING INTEGRATED MCDM UNDER NEUTROSOPHIC ENVIRONMENT

In material handling, warehousing, manufacturing and construction applications, forklifts are vital equipment, which are used to engage, lift and move palletized items. So, selection of the most appropriate forklift is an essential task for transportation of materials in warehouses for optimal use of the equipment. The present treatise introduces a well-known multi-criteria decision making (MCDM) technique, namely fully consistent method (FUCOM) under neutrosophic environment (NE) to model and solve the problem of selecting the best forklift for warehouse. In this regard, the linguistic assessments of the criteria have been represented in terms of single valued triangular neutrosophic numbers (SVTNNs). A novel triangular neutrosphic score function and ranking function are also proposed. To calculate criteria weights, a novel SVTN linear programming problem (SVTNLPP) has been developed. The alternatives have been ranked through multi-objective optimization on the basis of ratio analysis (MOORA). The robustness, consistency and reliability of the proposed integrated method have been checked through comparative and sensitivity analyses. This study makes a significant contribution by developing an original integrated model which provides warehousing system managers a quantifiable analysis, based on which they may make future decisions in order to improve the overall efficiency of the organization in transport handling

Multiple-Criteria Decision Making

Decision-making on real-world problems, including individual process decisions, requires an appropriate and reliable decision support system. Fuzzy set theory, rough set theory, and neutrosophic set theory, which are MCDM techniques, are useful for modeling complex decision-making problems with imprecise, ambiguous, or vague data.This Special Issue, “Multiple Criteria Decision Making”, aims to incorporate recent developments in the area of the multi-criteria decision-making field. Topics include, but are not limited to:- MCDM optimization in engineering;- Environmental sustainability in engineering processes;- Multi-criteria production and logistics process planning;- New trends in multi-criteria evaluation of sustainable processes;- Multi-criteria decision making in strategic management based on sustainable criteria

Application of a D Number based LBWA Model and an Interval MABAC Model in Selection of an Automatic Cannon for Integration into Combat Vehicles

A decision making procedure for selection of a weapon system involves different, often contradictory criteriaand reaching decisions under conditions of uncertainty. This paper proposes a novel multi-criteria methodology based on D numbers which enables efficient analysis of the information used for decision making. The proposed methodology has been developed in order to enable selection of an efficient weapon system under conditions when a large number of hierarchically structured evaluation criteria has to be processed. A novel D number based Level Based Weight Assessment – Multi Attributive Border Approximation area Comparison (D LBWA-MABAC) model is used for selection of an automatic cannon for integration into combat vehicles. Criteria weights are determined based on the improved LBWA-D model. The traditional MABAC method has been further developed by integration of interval numbers. A hybrid D LBWA-MABAC framework is used for evaluation of an automatic cannon for integration into combat vehicles. Nine weapon systems used worldwide have been ranked in this paper. This multicriteria approach allows decision makers to assess options objectively and reach a rational decision regarding the selection of an optimal weapon system. Validation of the proposed methodology is performed through sensitivity analysis which studies how changes in the weights of the best criterion and the elasticity coefficient affect the ranking results

AN EXTENDED SINGLE-VALUED NEUTROSOPHIC AHP AND MULTIMOORA METHOD TO EVALUATE THE OPTIMAL TRAINING AIRCRAFT FOR FLIGHT TRAINING ORGANIZATIONS

Aircraft’s training is crucial for a flight training organization (FTO). Therefore, an important decision that these organizations should wisely consider the choice of aircraft to be bought among many alternatives. The criteria for evaluating the optimal training aircraft for FTOs are collected based on the survey approach. Single valued neutrosophic sets (SVNS) have the degree of truth, indeterminacy, and falsity membership functions and, as a special case, neutrosophic sets (NS) deal with inconsistent environments. In this regard, this study has extended a single-valued neutrosophic analytic hierarchy process (AHP) based on multi-objective optimization on the basis of ratio analysis plus a full multiplicative form (MULTIMOORA) to rank the training aircraft as the alternatives. Moreover, a sensitivity analysis is performed to demonstrate the stability of the developed method. Finally, a comparison between the results of the developed approach and the existing approaches for validating the developed approach is discussed. This analysis shows that the proposed approach is efficient and with the other methods