An Interval Assignment Problem with Multiple Attributes: A DEA-Based Approach

One of the basic combinatorial optimization problems is the assignment problem that deals with assigning jobs to individuals. In traditional assignment problems, n jobs usually assign to n individuals such that the total cost is minimized or the total profit is maximized. However, in numerous real-life applications, various attributes could be considered in assignment problems while data (objective function coefficients) may be uncertain. Therefore, in the current paper, interval factors are taken in assignment problems where multiple attributes, inputs and outputs, present. Indeed, an approach based on Data Envelopment Analysis (DEA) is proposed to solve the interval assignment problem with multiple attributes. To illustrate, the non-parametric technique (DEA) is utilized to specify the lower and upper bounds of the best final efficiency scores of an assignment plan. Also, the method suggested herein is illustrated and clarified by an application.