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Projects and industrial activities developed by human beings generally affect their surroundings. For this reason, the efficacy of Environmental Impact Significance Assessment (EISA) method is increasingly demanded. There are multiple criteria involved in EISA problems that interact each other and may have either quantitative or qualitative nature. Classical approaches for EISA are not efficient in managing either uncertainty or different types of information, and the results obtained are numerical values difficult to interpret. The complexity of such problems and the uncertain information involved imply that experts sometimes hesitate among several values to express their assessments over criteria and they do not want to provide just one value, because it cannot reflect their hesitation. This brings about incomplete data in the experts' assessments. In order to deal with such situations, the concepts of hesitant fuzzy sets and hesitant fuzzy linguistic term sets have recently been introduced in quantitative and qualitative contexts respectively. Therefore, the aim of this paper is to define an EISA approach that allows managing heterogeneous information, including hesitant information. This approach provides a flexible evaluation framework in which experts can express their assessments, using different information domains that are unified in a linguistic domain by the 2-tuple linguistic model. It also obtains accurate results, which are easy to understand and interpret.

A Hesitant Heterogeneous Approach for Environmental Impact Significance Assessment