Nowadays, selection of an optimal project has become a challenging task for managers and decision makers. Project selection for a decision maker can be viewed as a complicated multicriteria decision making (MCDM) problem, which requires consideration of a number of conflicting, tangible and intangible selection criteria. Moreover, decision makers tend to use linguistic terms for expressing their assessments because of their different backgrounds and preferences, some of which may be uncertain and incomplete. Hence, this paper focuses on developing a hybrid fuzzy MCDM approach by combining AHP and VIKOR for solving the project selection problem. Finally, A numerical example is proposed to illustrate an application of the proposed method.

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This paper presents a multi-objective assignment problem (MAP) with interval parameters. Here, the model concentrates on three criteria: total cost, total profit and total operation time of assignment. The proposed model is classified as a nonlinear programming, in which it is difficult to solve. Hence, the model is converted into crisp linear programming problem by applying a substitution variables approach. In addition, a weighted min-max method is applied to transform the multi-objective problem into a single objective optimization problem. Finally, several numerical examples are provided to illustrate the implementation of the proposed approach. The results clearly provide some evidences that the proposed approach was easier to contrast compared with other approaches. The results also indicate that decision makers' preferences over various objectives could influence on solutions.