Lignocellulosic biomass is considered as one of the most promising feedstocks for producing fuel ethanol because of its global availability and environmental benefits of its use. In this paper, the process of lignocellulosic ethanol production was investigated at its present state of development. The experimental data from the East China University of Science and Technology were used to develop a process model and evaluate the performance of the whole process design. For the process simulation, all relevant information about the process streams, physical properties, and mass and energy balances were also considered. Energy integration is investigated to identify the best ways to supply heat to the process, realizing also combined heat and power production from wastewater and residue treatment. The sensitivity on ethanol yield and the overall system performance are also investigated.

Hesitant fuzzy linguistic term sets (HFLTSs) are very useful for dealing with the situations in which the decision makers hesitate among several linguistic terms to assess an alternative. Some multi-criteria decision-making (MCDM) methods have been developed to deal with HFLTSs. These methods are derived under the assumption that the decision maker is completely rational and do not consider the decision maker's psychological behavior. But some studies about behavioral experiments have shown that the decision maker is bounded rational in decision processes and the behavior of the decision maker plays an important role in decision analysis. In this paper, we extend the classical TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making) method to solve MCDM problems dealing with HFLTSs and considering the decision maker's psychological behavior. A novel score function to compare HFLTSs more effectively is defined. This function is also used in the proposed TODIM method. Finally, a decision-making problem that concerns the evaluation and ranking of several telecommunications service providers is used to illustrate the validity and applicability of the proposed method.

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