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The purpose of this paper is to propose a new integrated method for evaluating inventory of slow-moving items by introducing the application of fuzzy AHP method with interval Type-2 fuzzy sets (IT2FSs) and ABC analysis.

In the study, fuzzy analytic hierarchy process (AHP) method with IT2FSs is employed to set the importance of criteria. The weights obtained from IT2 fuzzy AHP are used to classify slow-moving items in ABC analysis. In the application part, a real-life case study is presented.

The result of this study indicates that an integrated approach utilizing IT2 fuzzy AHP and ABC analysis can be used as a supportive tool for classification of slow-moving items. The problem is solved under fuzzy environment to handle uncertainties and lack of information about slow-moving items.

Actual data are provided from an automotive company for prioritizing a various criteria to evaluate and classify stocks and a hypothetical model integrated with IT2 fuzzy AHP and ABC analysis is demonstrated.

Apart from inventory classification literature, the study integrates fuzzy AHP method by employing interval IT2FSs and ABC analysis to solve the real-life inventory classification problem.

The purpose of this paper is to develop a systematic and comprehensive project selection model utilizing fuzzy multi-objective linear programming (FMOLP) that deals with the imprecise data in IS projects and uncertain judgment of decision makers.

First, projects are prioritized by considering both quantitative and qualitative factors. A fuzzy analytical hierarchical process (FAHP) is used in order to obtain weights of each project that indicates their priorities. At the second step, project selection decision is completed by using FMOLP. Then, the sensitivity analysis is performed to evaluate the robustness of the proposed integrated model.

The result of this study indicates that an integrated approach utilizing FAHP and FMOLP can be used as a supportive tool for project selection in IS context. It decreases the uncertainty caused from uncertain judgment of decision makers.

Future studies are suggested to design models having fuzzy constraints such as budget and resources. Moreover, for future studies, non-linear membership functions can be used.

Actual projects are provided from the Turkish IS company for prioritizing process and a hypothetical mathematical model is demonstrated using illustrative data.

This study contributes to the relevant literature by proposing a comprehensive model considering many conflicting ideas of decision makers on quantitative and qualitative criteria, and evaluating projects in an integrated way including FAHP and FMOLP.