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

Training Aircraft Selection of the Vietnam People's Air Force Using a Hybrid BWM-Fuzzy TOPSIS Method

Demands that the Vietnam People's Air Force (VPAF) have new modern training aircraft have been growing recently. Although other training aircraft such as the Yak-52 and L-39 have performed well for decades, they are no longer able to perform the full range of training tasks required of them due to an increasing technology gap. In 2016, the United States government lifted a decade-long ban on lethal arms sales for Vietnam. This has created opportunities for Vietnam to access a variety of weapons suppliers from many countries that have a strong, global defence industry. However, one of the most difficult decisions the VPAF must make concerns the type, configuration, and capabilities of future training aircraft. This study therefore proposes a Multi-Criteria Decision Making (MCDM) model by combining the Best Worst Method (BWM) and a Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) to choose a modern training aircraft that can replicate the characteristics of several fourth-generation or better fighter planes, with the fifth-generation fighters also being able to perform light-attack and reconnaissance duties for VPAF. The case study employing the hybrid BWM-Fuzzy TOPSIS method reveals that the Yak-130 training aircraft is the best selection for VPAF. To validate the robustness of the proposed framework, sensitivity analysis has been conducted with the result compared to Analytic Hierarchy Process (AHP)

REGIONAL AIRCRAFT SELECTION WITH FUZZY PIPRECIA AND FUZZY MARCOS: A CASE STUDY OF THE TURKISH AIRLINE INDUSTRY

Aircraft selection is an important issue in achieving long-term goals in the airline industry. For this issue in which multiple conflicting criteria are involved, the extant literature points to the use of multi-criteria decision-making (MCDM) methods. In this respect, this study aims to propose a systematic and comprehensive framework with a focus on the regional aircraft selection perspective. To achieve this, an integrated fuzzy Pivot Pairwise Relative Criteria Importance Assessment (F-PIPRECIA) and fuzzy Measurement Alternatives and Ranking according to the Compromise Solution (F-MARCOS) approach was employed. In this study, in which six regional aircraft alternatives were evaluated according to 14 criteria, data were collected from five decision experts. As a result, it was found that the most pivotal criterion is C33 (Operational Cost), and the least important criterion is C12 (NOx). In addition, CRJ1000 was identified as the most promising regional aircraft alternative. The results of the application were further validated by applying a three-stage sensitivity analysis. The proposed structure is anticipated to assist airline managers in aircraft selection decisions under uncertainty by offering a robust and systematic tool

Mengenal pasti tahap motivasi dan kecenderungan keusahawanan di kalangan pelajar semester akhir Ijazah Sarjana Muda Kejuruteraan Mekanikal : satu tinjauan di KUiTTHO

Keusahawanan merupakan bidang yang mencabar dan tidak ramai yang mahu menceburi bidang ini tenitaraa lulusan bidang kejnriiteraan. Mereka ini mempunyai elemen keusahawanan nntuk menjadi usahawan yang beijaya. Oleh itu, timbul persoalan mengapakah pelajar-pelajar ini kurang berminat dengan bidang keusahawanan?. Bersesuaian dengan pennasalahan tersebut, kajian ini dijalankan bertujuan untnk meninjau tahap motivasi bagi memberikan pendedalian dan menarik kecenderungan pelajar kejuruteraan terliadap bidang keusahawanan. Objektif kajian ini berdasarkan kepada beberapa aspek iaitn taliap pengetahuan keusahawanan, motivasi, kecenderungan terhadap bidang keusahawanan dan keperluan subjek atau elemen keusahawanan dalam jumsan kejuruteraan. Kajian yang telah dijalankan adalah kajian deskriptif berbentuk tinjauan yang menggunakan soal selidik sebagai instrumen untuk mendapatkan data. Dengan menggimakan persampelan rawak mudah, seramai 99 orang pelajar semester akhir ijazah Saijana Muda Kejuruteraan Mekanikal telah dipilih sebagai responden kajian. Instrumen kajian adalah soal selidik dan data-data yang diperolehi telah dianalisis menggimakan perisian Statistical Package For Social Science versi 11.0 untuk mendapatkan nilai min dan peratus. Hasil kajian mendapati bahawa pelajar-pelajai' ini mempunyai kecenderungan terhadap bidang keusahawanan dengan skor min keseluruhan 3.573 dan taliap motivasi keusahawanan yang tinggi dengan skor min keseluaihan 3.965 tetapi kekurangan pengetahuan dalam bidang keusahawanan dengan skor min 3.16. Oleh itu. adalah perlu elemen-elemen keusahawanan diterapkan ke dalam kuriknlum kursus kejuaiteraan

Permutation based decision making under fuzzy environment using Tabu search

One of the techniques, which are used for Multiple Criteria Decision Making (MCDM) is the permutation. In the classical form of permutation, it is assumed that weights and decision matrix components are crisp. However, when group decision making is under consideration and decision makers could not agree on a crisp value for weights and decision matrix components, fuzzy numbers should be used. In this article, the fuzzy permutation technique for MCDM problems has been explained. The main deficiency of permutation is its big computational time, so a Tabu Search (TS) based algorithm has been proposed to reduce the computational time. A numerical example has illustrated the proposed approach clearly. Then, some benchmark instances extracted from literature are solved by proposed TS. The analyses of the results show the proper performance of the proposed method

A Fuzzy Based Decision Making Approach for Selecting and Evaluating Green Suppliers

In a competitive business environment, green supplier selection approach plays a pivotal role in supply chain management, because, due to growing global concern of environmental protection, green production has become an important factor for almost every manufacturer and will influence the sustainability of a manufacturer in the long run. A performance evaluation system for green suppliers is therefore required to determine the suitability of suppliers to cooperate with the industry. Supplier selection is basically depends on decision makers’ (experts’) assessments. This process inevitably involves various types of uncertainties such as deception, fuzziness and incompleteness due to the shortcomings of the human being’s subjective judgment and it’s variance from one human being to another. However, the existing methods cannot properly integrate uncertainties into the determination of green suppliers and their selection. Nowadays, many companies have begun to implement green supply chain management and to consider environmental issues and the measurement of their suppliers’ environmental performance. Here we have adopted, an effective method for selecting and evaluating green supplier selection; TOPSIS (Technique for order preference by similarity to Ideal Solution

Training and Development Need Ranking of a Hotel Manager using Fuzzy Technique for Order Preference by Similarity to Ideal Solution

Regular training and development programs are necessary to learn or improve skills and knowledge of the employees, as it has long term positive effect on the prosperity or success of the organization. For this, organization searches out the employees to whom training may be given as per their need. As every organization has different needs, various criteria and alternatives are determined by the group of decision makers. In this paper, multi-criteria group decision making model is considered, where various training and development needs of a hotel manager have been identified by group of decision makers and ranked with simplified fuzzy technique for order preference by similarity to ideal solution (Fuzzy TOPSIS) method. Results are reported with application on the basis of closeness coefficient using triangular and trapezoidal fuzzy number. Results showed that the ranking by Fuzzy TOPSIS is same, by using triangular and trapezoidal fuzzy number and can be successfully used to rank the appropriate training and development need required by the manager of hotel

Integration of fuzzy Shannon’s entropy with fuzzy TOPSIS for industrial robotic system section

Purpose: The aim of this study is applying a new method for Industrial robotic system selection. Design/methodology/approach: In this paper, the weights of each criterion are calculated using fuzzy Shannon’s Entropy. After that, fuzzy TOPSIS is utilized to rank the alternatives. Then we select the best Industrial Robotic System based on these results. Findings and Originality/value: The outcome of this research is ranking and selecting industrial robotic systems with the help of Fuzzy Shannon’s Entropy and Fuzzy TOPSIS techniques. Originality/value: This paper offers a new integrated method for industrial robotic system selection.Peer Reviewe

APPLICATION OF TOPSIS METHOD WITH TRAPEZOIDAL FUZZY NUMBERS

The article is devoted to the problem of multi-criteria decision making. As application problem is used the equipment selection problem. The analysis of existing methods for solving this problem is given. As a method for solving this problem fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) is proposed. This method is based on ideal solution approach. The issues of practical implementation of this method are discussed in details. The results of the solution test problem at all stages are presented.The article is devoted to the problem of multi-criteria decision making. As application problem is used the equipment selection problem. The analysis of existing methods for solving this problem is given. As a method for solving this problem fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) is proposed. This method is based on ideal solution approach. The issues of practical implementation of this method are discussed in details. The results of the solution test problem at all stages are presented

Evaluating high risks in large-scale projects using an extended VIKOR method under a fuzzy environment

The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM) methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment