Hazardous waste management is increasingly becoming a concern, especially for hazardous waste generators (HWG), as hazardous waste may pose risks to human health and/or its environment if handled improperly. To better address these issues, stakeholders frequently choose to outsource the waste transportation process in order to ensure a clean environment and minimize the cost of transportation of the hazardous waste. Regulatory compliance and cost aspects shall be considered when selecting the best Hazardous Waste Carrier (HWC), making it a standalone decision problem for HWG. The safety aspects of hazardous waste transportation (HWT) is a priority, therefore the evaluation and identification of the most suitable HWC is a key subject for HWG. This decision is affected by various elements, many of which are highly vague and imprecise that need to be assessed by several experts from different backgrounds. The evaluation of various criteria for many alternatives by a group of decision makers (DMs) makes this process a multi-criteria decision-making (MCDM) problem under group decision making (GDM). Up to now, different methods are applied by researchers to select the best available alternative among others. The applied techniques either used precise numerical values for selection criteria or membership functions of classical fuzzy. Such techniques prove inadequate in the presence of uncertainty and vagueness. This paper addresses this HWC selection process by proposing a logical, systematic and integrated MCDM method based on Analytical Hierarchy Process (AHP) and Visekriterijumsko kompromisno rangiranje (VIKOR) under intuitionistic fuzzy (IF) environment. In addition, a GDM approach is used with IF in order to avoid bias, overcome uncertainties and minimize the partiality of decision making processes. The proposed integrated framework's usefulness is demonstrated with a real case study from Turkey. Thus, this study presents innovative research elements by introducing a combined IF AHP and IF VIKOR framework for the first time and developing an evaluation model for a real industrial problem to improve the HWC selection process. (C) 2018 Elsevier Ltd. All rights reserved.