Transportation systems play a key role in urban development by providing access for people to markets and education, employment, health care, recreation, and other key services. However, uncontrolled urban population and fast growth of vehicle mobility inevitably lead to unsustainable urban transportation systems in terms of economic, technical, social, and geographical aspects of sustainability. Thus, there is a need to select suitable sustainable urban transportation (SUT) alternatives, which can contributed to the technological advancement of a city and changes in societal necessities, mitigating the climate change impact from transport and transforming living habits, in the context of high urban population growth. Therefore, this paper aims to introduce an integrated multi-attribute decision analysis (MADA) framework for assessing and ranking the sustainable urban transportation (SUT) options under an intuitionistic fuzzy sets (IFSs) context. In this regard, firstly IF-distance measures and their properties are developed to obtain the criteria weight. Second, an IF-relative closeness coefficient-based model is presented to find the criteria weights. Third, the operational competitiveness rating (OCRA) model is introduced with the IF-score function-RS-based decision experts’ weighing model and the relative closeness coefficient-based criteria weight determination model under the IFSs environment. To exemplify the utility and effectiveness of the developed IF-relative closeness coefficient-based OCRA methodology, a case study ranking the different SUT bus options is presented from an intuitionistic fuzzy perspective. A comparison with different models is made to prove the superiority and solidity of the obtained outcome. Moreover, the comparative analysis outperforms the other extant MADA models, as it can provide more sound outcomes than others, and thus it is more suitable and efficient to elucidate uncertain information in handling practical MADA problems. In this study, we analyze and determine the most suitable and sustainable SUT by considering the economic, technical, environmental, and social dimensions of sustainability and also make a significant contribution to the current scientific knowledge by providing a novel decision support system from an uncertainty perspective.

As an alternative for sustainable transportation and economic development, biofuels are being promoted as renewable and climate-friendly resources of energy which can help to reduce the consumption of fossil fuels, some pollutant emissions and mitigate the climate change impact from transport. With the successful development of the biofuel industry, the location selection for biofuel production plant is one of the major concerns for the governments and policymakers. Finding locations for the construction of new biofuel production plants includes several dimensions of sustainability, including economic, social and environmental; therefore, this selection process can be considered a complex multi-criteria decision-making problem with uncertainty. As an advanced version of fuzzy set, picture fuzzy set (PiFS) is one of the comprehensive tools to handle the uncertainty with the account of truth, abstinence and falsity membership degrees. Thus, this work proposes a new decision-making methodology based on the weighted aggregated sum product assessment (WASPAS) approach and similarity measure with picture fuzzy information. By using picture fuzzy numbers, the proposed methodology can effectively address the uncertain information and qualitative data that often occurs in practical applications. In this methodology, a picture fuzzy similarity measure-based weighting model is proposed to find the criteria weights under picture fuzzy environment. For this purpose, a new similarity measure is introduced to measure the degree of similarity between picture fuzzy numbers. Moreover, the rank of the options is determined based on an integrated WASPAS approach under a PiFS context. To illustrate the effectiveness of the proposed framework, a case study of biofuel production plant location selection is presented from the picture fuzzy perspective. Further, a comparison with existing methods is conducted to test the validity and applicability of the obtained results. The sensitivity analysis is performed with respect to different values of decision parameter, which proves the stability, robustness, and practicality of the proposed approach. The presented picture fuzzy WASPAS approach feasibly enables the policymakers to identify the most desirable location for a biofuel production plant by considering the social, environmental and economic aspects of sustainability.