(2002). Evaluation and Decision Models: a Critical Perspective. Journal of the Operational Research Society: Vol. 53, No. 7, pp. 809-809.

/pdf/evaluation-and-decision-models-a-critical-perspective-4d2dtonb5u.pdf

Evaluation and Decision Models: a Critical Perspective

Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control Iran is one of the most seismically active countries in the world The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1 The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95% A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies

Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

University chemical laboratory is a high-risk place for teaching and scientific research due to the presence of various physical and chemical hazards. In recent years, university chemical laboratory accidents occur frequently. This urges the need to enhance university chemical lab safety. A semi-quantitative methodology comprising Matter-Element Extension Theory (MEET) implemented with Combination Ordered Weighted Averaging (C-OWA) operator is proposed to assess the risk of a university chemical laboratory. First, an index-based risk assessment system of university chemical laboratory is built by identifying various risk factors from a system perspective. Then, C-OWA operator is used to calculate the weight of assessment indices, whereas MEET is employed to determine the correlation degree of assessment indices. Finally, the comprehensive risk of university chemical laboratories is assessed, and some safety measures are proposed to reduce the risk of university chemical laboratories. The applicability of the proposed methodology is tested using a practical case. It is observed that the methodology can be a useful tool for risk assessment and management of university chemical laboratories.

A semi-quantitative methodology for risk assessment of university chemical laboratory

Purpose The purpose of current analytical work is to identify the critical barriers in social isolation in India amid Coronavirus infection disease (COVID) outbreak using the fuzzy-analytical hierarchical process (AHP) method. Design/methodology/approach The conventional AHP is insufficient for tackling the vague nature of linguistic assessment. Fuzzy AHP had been developed to resolve the hierarchical fuzzy problems, avoiding its risks on performance. In AHP, all comparisons are not included;thus, to find the priority of one decision variable over other, triangular fuzzy numbers are used. Findings A total of eight critical barriers in social distancing in India during COVID-19 have been compared and ranked. Dense population has emerged as the most culpable barrier in social isolation in India amid COVID outbreak followed by compulsion for pecuniary earning and general incautiousness. A total of eight critical barriers in social distancing in India during COVID-19 in four categories (societal barriers, insufficient facilitation barriers, growth-related barriers and population related barriers) have been compared and ranked. Originality/value On the basis of the numeral values, growth-related barriers" attained top position followed by "population-related barriers" and "insufficient facilitation barriers." The current work has explored the possible factors which can become key game changers to control the pace of spread of the pandemic."

Multi-criteria analysis of social isolation barriers amid COVID-19 using fuzzy AHP

COVID-19 has severely damaged the social values and economic values of global supply chain. This unprecedented pandemic acts as hindrance in the path of sustainable development goals that are to be achieved by 2030. This study focuses on the disruption that has taken place due to COVID outbreak and also identifies the role of sustainable finance in achieving sustainable supply chain. This study highlighted the critical factors that are important to adapt the sustainable supply chain. A case study of food industry has been performed to prioritize the critical factors with the help of MCDM techniques. Major criteria and sub-criteria that play a crucial role in sustainable supply chain finance have been listed here. This study contributes in the area of sustainable supply chain and how finance can play a major role in achieving sustainable supply chain and ultimately sustainable development goals. The findings of this study show that social values of any industry are the most crucial asset for any organization.

/pdf/a-decision-making-framework-for-sustainable-supply-chain-3xi6uviuyg.pdf

A Decision-Making Framework for Sustainable Supply Chain Finance in Post-COVID Era

The readymade garments industry is rapidly growing and now it is the single highest export earner for Bangladesh. This business sector becomes an attractive investment destination to the country’s new young entrepreneurs upcoming due to its cheaper labor cost, lower investment cost, availability of resources, governments support, etc. than the other sectors. However, many other factors are often needed to consider in investing in this garments sectors. Again, in garments sectors, there is a wide range of apparel items like shirts, trousers, jackets, sweaters, etc. options that are available to invest. Different types of apparel items demand different types of resource requirements, diverse level of capital investment, operator’s skills, and it is also related to the many other factors. Again, all the investors are not in same stand points according to their business handling capabilities, capitals in hand, business locations and so many other aspects. This paper proposes a methodology for selection best apparel item among different alternatives that will provide a decision support to the investors in opening a new garment factory. The proposed methodology is based on Analytical Hierarchy Process (AHP) under fuzzy environment. The approaches allow the decision maker to use expert’s judgment in the form of linguistic expression in the evaluation process. In the application of proposed methodology, the best apparel item is selected for opening a garment factory in Bangladesh at present conditions.

http://www.riejournal.com/article_58089_ca611b1095cefb0f3c785e3c73665dcf.pdf

A Fuzzy-AHP Method for Selection Best Apparel Item to Start-Up with New Garment Factory: A Case Study in Bangladesh

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A Fuzzy-AHP Method for Selection Best Apparel Item to Start-Up with New Garment Factory: A Case Study in Bangladesh