Already faced with tight competition and low profit margins, the airline industry is going through major changes in the wake of the current pandemic resulting in travel restrictions and slump demands, prompting airlines to curtail services and investments in every aspect of business. To that end, developing a comprehensive method of improving airline performance measures is crucial. However, this type of problem is complex to solve due to a large number of factors, requiring a systematic approach. It entails taking into account a multitude of conflicting, or sometimes interrelated criteria, hence becoming an inherently multiple criteria decision making problem. This study is aimed to assess the competitiveness of airlines and evaluate their financial and operational performances in relation to such criteria. We test FAHP, TOPSIS, and a hybrid method of combining FAHP and TOPSIS methods. In particular, regarding the hybrid method, FAHP is employed to determine the influential weights of criteria that are utilized in TOPSIS for preference values among alternatives. We demonstrate the applicability of the proposed methods to solving a MCDM problem of airline performance assessments using real data sets. Further, this study focuses on examining the relationship between financial and operational performance criteria, as well as gleaning insights for airlines to build an evaluation system that would aid in understanding their strength and weakness in the performance metrics. The computational experiment results of our hybrid FAHP-TOPSIS model support the efficacy of incorporating fuzzy values concerning influential weight criteria. By judiciously distributing criteria weights that are specific to the airline industry, our proposed model captures preference scores reflective of industry-related and concurrent measures. This modeling framework can help airlines better evaluate the systematic influential relation structure among criteria in critical financial and operational dimensions.

The COVID-19 outbreak has illustrated the wide range of issues that supply networks confront when they are subjected to major interruptions. The supply networks for vaccines are no exception. To get out of this pandemic, it's critical to identify and address problems with the COVID-19 vaccine supply chain (VSC). This work identifies 13 challenges and prioritizes those. The findings provide stakeholders and government policymakers with realistic advice for developing a better VSC. This paper proposes a methodology based on fuzzy analytical hierarchy process (Fuzzy-AHP) with the use of triangular fuzzy numbers for prioritizing VSC barriers. It has been found that the impact of poor health worker training facilities becomes maximum with the highest weightage. Moreover, the managerial implication of the results is also provided, which will be useful for VSC sectors to take suitable decisions to overcome these obstacles.

This paper considered a case of supplier selection problem in a glove manufacturer located at Yogyakarta, Indonesia that uses genuine sheep leather as the raw material. The problem is solved using both Analytical Hierarchy Process (AHP) and Fuzzy AHP, in which three versions of Fuzzy AHP are applied i.e. Extent Analysis proposed by Chang (1996) [Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649-655.], Extent Analysis proposed by Wang (2008) [Wang, Y. M., Luo, Y., & Hua, Z. (2008). On the extent analysis method for fuzzy AHP and its applications. European Journal of Operational Research,186(2), 735-747.], and the modified Fuzzy LLSM proposed by Wang (2006) [Wang, Y. M., Elhag, T. M., & Hua, Z. (2006). A modified fuzzy logarithmic least squares method for fuzzy analytic hierarchy process. Fuzzy Sets and Systems, 157(23), 3055-3071.]. Moreover, the research is conducted by incorporated four expert respondents, who have more than 12 years of experience in the problem. It is found that the top four priorities obtained from AHP are similar with those from Fuzzy AHP with Extent Analysis proposed by Chang (1996) and Fuzzy AHP with the modified Fuzzy LLSM proposed by Wang (2006). This priority list of supplier can be used by the manufacturer to select the raw material supplier.

Effective transshipment network is currently recognized as an important success determinant for most manufacturing organizations, because the transshipment management has significant impact on cost and environmental impact. Due to the complexity of the multi-criteria transshipment problem for infectious waste management (IWM) for this case, forty hospitals and three candidate disposal municipalities in Northeastern Thailand, a novel holistic approach (combination of fuzzy AHP, transshipment model and DEA) was developed for solving this problem. We first utilized the fuzzy AHP technique to calculate the location weights of each candidate disposal municipalities. Secondly, a new cost-based transshipment model was formulated and solved in order to provide the set of feasible solutions. These solutions can be viewed as decision making units (DMUs), inputs and outputs. Finally, DEA-CCR model was applied to calculate the efficiency scores of candidate DMUs. The study results demonstrated that the proposed holistic approach can help decision makers (DMs) to choose a suitable transshipment network for IWM. The major advantage of the proposed holistic approach is that both costs and environmental impacts under constraints are focused on simultaneously. Future work will apply the developed approach with other real-world complex problems to enhance the validity of the research output further. For large-size transshipment problems in which an exact solution cannot be found, meta-heuristics must be applied.

This paper presents an empirical investigation to rank different factors influencing on maintenance strategies on Iranian oil terminals’ company. The study determines four main factors, production quality, reliability, cost and safety. Using fuzzy analytical process, the study determines various factors associated with each main factor and ranks them by performing pair-wise comparisons. The results indicate that reliability ranks first (0.255), followed by production quality (0.252), cost (0.25) and safety (0.244). In terms of reliability, the best utilization of resources is number one priority followed by increase access to maintenance tools, reduction in production interruption are among the most important issues. In terms of production quality, reduction in system failure as well as reworks is the most important factors followed by customer satisfaction and defects. In terms of cost items, ease of access to accessories and consulting are important factors followed by necessary software, hardware and training programs. Finally, in terms of safety factors, external, internal and employee services are the most important issues, which are needed to be considered.

The Human Development Index (HDI) is a composite statistic of life expectancy, education, and income indices, which is implemented to rank countries into different items of human development including life expectancy, education, living standards. This paper uses fuzzy analytical hierarchy process (AHP) to rank five influencing factors including income, culture, healthcare, knowledge and civil rights in Iran. Using a questionnaire in linguistic form, the study asks some experts to make judgment about the relative importance of each pair of five items and it ranks them based on fuzzy AHP technique. The results indicate that income is number priority followed by knowledge, culture, civil rights and healthcare affairs.

Strategic warehouse location-allocation problem is a multi-staged decision-making problem having both numerical and qualitative criteria. In order to survive in the global business scenario by improving supply chain performance, companies must examine the cross-functional drivers in the optimization of logistic systems. A meticulous observation makes evident that strategy warehouse location selection has become challenging as the number of alternatives and conflicting criteria increases. The issue becomes particularly problematic when the conventional concept has been applied in dealing with the imprecise nature of the linguistic assessment. The qualitative decisions for selection process are often complicated by the fact that often it is imprecise for the decision makers. Such problem must be overcome with defined efforts. Fuzzy multi-criteria decision making methods have been used in this research as aids in making location-allocation decisions. The anticipated methods in this research consist of two steps at its core. In the first step, the criteria of the existing problem are inspected and identified and then the weights of the sector and subsector are determined that have come to light by using Fuzzy AHP. In the second step, eligible alternatives are ranked by using TOPSIS and Fuzzy TOPSIS comparatively. A demonstration of the application of these methodologies in a real life problem is presented.

The main objective of this study is to identify the most important criteria and indicators in selection of business intelligence vendors, and ranking the vendors of such tools using Fuzzy Analytical hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), to compare results of these two methods and to provide appropriate solutions for the sample company, namely National Iranian Oil Company (NIOC).
Spearman & apos; s rank correlation test was used for comparing the methods and determining their correlation. A strong positive correlation was observed between the ranks of business intelligence tools at the significance level of 0.05 in both methods. The results of the ranking by means of FAHP method show that IBM Company was the best one, followed by Oracle, SAS, QlikTech, SAP and Microsoft. However, based on the FTOPSIS method, Oracle was the leading company, followed by IBM, SAS and SAP and finally Microsoft.

Due to increasing penetration of internet connectivity, on-line retail is growing from the pioneer phase to increasing integration within people & apos; s lives and companies & apos; normal business practices. In the increasingly competitive environment, on-line retail service providers require systematic and structured approach to have cutting edge over the rival. Thus, the use of benchmarking has become indispensable to accomplish superior performance to support the on-line retail service providers. This paper uses the fuzzy analytic hierarchy process (FAHP) approach to support a generic on-line retail benchmarking process. Critical success factors for on-line retail service have been identified from a structured questionnaire and literature and prioritized using fuzzy AHP. Using these critical success factors, performance levels of the ORENET an on-line retail service provider is benchmarked along with four other on-line service providers using TOPSIS method. Based on the benchmark, their relative ranking has also been illustrated.

Carpet is one of the most popular handcraft industries in Iran and it has created significant number of jobs in various villages and small towns in this country. There are literally many designs and plans introduced by Iranian carpet makers but during the past two decades, we have seen an increasing competition mostly from other countries such as China, India, Pakistan, etc. On the other hands, there are ongoing interests for membership of world trade organization (WTO) and it is necessary to take the necessary actions. The proposed study of this paper uses different mathematical techniques to consider different actions for changing threats to opportunities, reducing unnecessary costs, increasing revenue and market share, etc. The proposed model of this paper uses Fuzzy analytical hierarchy process (AHP), Benefits-Opportunities-Costs-Risks (BOCR) method to detect possible benefit, risk and cost components. We first setup all useful strategies and then using AHP prioritizes different actions.