Wyniki wyszukiwania - BazTech

1

A Z-number and MABAC method based on reliability analysis and evaluation of product design concept

Tan Yuhang, Chen Zhe, Wang Baoping, Ma Qing, Wei Jianing

Eksploatacja i Niezawodność

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2024

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Vol. 26, no. 1

art. no. 178304

EN

Modular design is a significant method for complicated product development. In the context of modular design, involving users in concept assessment boosts a product's appeal but also introduces decision uncertainty and unreliability. As a solution, this paper proposed a hybrid method by integrating expert consensus modeling, attribute weighting, Z-number, and the Multi-Attribute Border Approximation Area Comparison (MABAC) method. Initially, a consensus model is established using consistency theory to determine expert weights, and attribute priorities are determined through the entropy weighting method. Subsequently, the Z-number-based MABAC method ranks the alternatives, determiningthe optimal solution among them. Using an automated outdoor cleaning vehicle as an example, the proposed method is compared to other techniques. The sensitivity analysis and the comparisons show that the proposed method improves the reliability and objective of the decision-making process.

2

Determining the logistics market performance of developing countries by entropy and MABAC methods

Kara Karahan, Bentyn Zbigniew, Yalçın Galip Cihan

LogForum

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2022

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Vol. 18, no. 4

421--434

EN

Background: The levels of logistics market performance of developing countries are published with Agility Emerging Markets Logistics Index (AEMLI) reports. The main purpose of this research is to propose a new model to determine the logistics market performance of developing countries in 2022 and to reorder the developing countries according to their logistics market performance. Methods: AEMLI indicators have been accepted as the basic criteria for determining the logistics market performance. The importance levels of these criteria have been determined by the Entropy technique. The logistics market performance rankings of developing countries according to the criteria were determined using the Multi-Attributive Border Approximation Area Comparison (MABAC) technique. The data set of 50 developing countries included in the 2022 AEMLI report has been used in the investigation. Results: According to the proposed new model, the weights of the criteria and logistics market performance rankings of developing countries have been determined. The importance levels of the criteria have been determined as Business Fundamentals (BF), Digital Readiness (DR), International Logistics Opportunities (ILO), and Domestic Logistics Opportunities (DLO), respectively. The ranking based on the new model was compared with the rankings in the 2022 AEMLI report. 21 of the 50 developing countries have improved their rankings. The ranking of 20 countries has been dropped. There is no change in the ranking of 9 countries. Additionally, according to AEMLI, the country with the highest logistics market performance is China, while the country with the best logistics market performance according to the proposed model is the United Arab Emirates (UAE). Conclusions: Contrary to the literature, Entropy and MABAC techniques were used to rank the logistics market performances of developing countries by making use of AEMLI reports. The issues that countries should focus on in the development of their logistics market performance are shown.

3

The assessment of the logistics performance index of CEE countries with the new combination of SV and MABAC methods

Isik Ozcan, Aydin Yuksel, Kosaroglu Serife Merve

LogForum

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2020

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Vol. 16, no. 4

549--559

EN

Background: The increase in global trade has caused logistics activities to be an important tool in providing strategic competitive advantage on a global scale. The logistics industry, which helps to facilitate the activities related to the movement of goods in the supply chain, is one of the fastest-growing sectors and has important effects on the economic performance of the countries. Measuring and evaluating the logistics performance of countries can enable them to reach their goals of achieving sustainable competitive advantage by revealing the strengths and weaknesses of logistics services in the entire supply chain. In this regard, the purpose of this study is to analyze and rank logistics performance in terms of selected 11 Central and Eastern European Countries (CEECs). Methods: In this study, the SV (Statistical Variance) and the MABAC (Multi-Attributive Border Approximation area Comparison) methods are used to form a decision-making model in evaluating the logistic performance. In logistics performance evaluation, the SV method is used to weight the selected performance criteria, whereas the MABAC method is employed to evaluate and rank the logistics performance of CEECs. Results: The results obtained from the SV method demonstrates that timeliness and infrastructure are the most and least significant performance criteria, respectively. According to the performance ranking of the countries by the MABAC method, the countries in the top three rankings are the Czech Republic, Poland and Hungary, respectively. Conclusions: The fact that the ranking of the proposed hybrid model is the same as the original logistics performance index (LPI) ranking of the selected countries suggests that the proposed model is consistent.

PL

Wstęp: Wzrost globalnego handlu jest przyczyną wzrostu ważności działalności logistycznej jako narzędzia służącego do uzyskiwania przewagi konkurencyjnej na globalną skalę. Branża logistyczna, która wspomaga wszelkie czynności związane z przepływem towarów w obrębie łańcucha dostaw, jest jednym z najszybciej rosnących sektorów i ma istotny wpływ na ekonomiczne wyniki krajów. Pomiar oraz ocena sprawności logistycznej krajów umożliwia im osiągnięcie postawionych celów w uzyskaniu zrównoważonej przewagi konkurencyjnej poprzez ujawnienie słabych i mocnych stron swoich usług logistycznych w obrębie całego łańcucha dostaw. Celem pracy jest analiza i stworzenie rankingu działalności logistycznej wybranych 11 krajów Europy Środkowo-Wschodniej. Metody: W pracy zastosowano metody SV (Statistical Variance) oraz MABAC (Multi-Attributive Border Approximation area Comparison) dla zbudowania modelu podejmowania decyzji odnośnie oceny działalności logistycznej. Dla oceny działalności logistycznej, metoda SV została zastosowana do wyznaczenia wagi poszczególnych kryteriów oceny, podczas gdy metoda MABAC została używana do oceny i tworzenia rankingu działalności logisty stycznej krajów Europy Środkowo-Wschodniej. Wyniki: Wyniki uzyskane przy użyciu metody SV pokazują, że terminowość oraz infrastruktura jest najważniejszymi kryteriami oceny działalności. Zgodnie ze stworzonym rankingiem przy pomocy metody MABAC, najwyżej ocenionymi krajami były: Czechy, Polska i Węgry. Wnioski: Ranking uzyskany za pomocą opracowanej metody jest taki sam jak przy użyciu oryginalnego współczynnika działalności logistycznej (LPI), co dowodzi poprawności wypracowanego modelu.

4

Interval-valued Fuzzy Soft Decision Making Methods Based on MABAC, Similarity Measure and EDAS

Peng X., Dai J., Yuan H.

Fundamenta Informaticae

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2017

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Vol. 152, nr 4

373--396

EN

Interval-valued fuzzy soft decision making problems have obtained great popularity recently. Most of the current methods depend on level soft set that provide choice value of alternatives to be ranked. Such choice value always encounter the equal condition that the optimal alternative can't be gained. Most important of all, the current decision making procedure is not in accordance with the way that the decision makers think about the decision making problems. In this paper, we initiate a new axiomatic definition of interval-valued fuzzy distance measure and similarity measure, which is expressed by interval-valued fuzzy number (IVFN) that will reduce the information loss and keep more original information. Later, the objective weights of various parameters are determined via grey system theory, meanwhile, we develop the combined weights, which can show both the subjective information and the objective information. Then, we present three algorithms to solve interval-valued fuzzy soft decision making problems by Multi- Attributive Border Approximation area Comparison (MABAC), Evaluation based on Distance from Average Solution (EDAS) and new similarity measure. Three approaches solve some unreasonable conditions and promote the development of decision making methods. Finally, the effectiveness and feasibility of approaches are demonstrated by some numerical examples.