A multiplier form of slacks-based measure model in stochastic data envelopment analysis
by Mohammad Hossein Tavassoli; Ali Asghar Foroughi
International Journal of Management and Decision Making (IJMDM), Vol. 21, No. 3, 2022

Abstract: Data envelopment analysis (DEA) is a mathematical approach based on linear programming, which evaluates the rational efficiency of decision-making units (DMUs) with multiple inputs and outputs. In conventional DEA, the data values are considered to be deterministic. However, the data might be non-deterministic in nature, and DMUs evaluation within DEA may be sensitive to imprecise data. An approach to deal with imprecise data is considering stochastic data within DEA. In this paper, chance constrained programming (CCP) concept is applied to develop slacks-based measure (SBM) multiplier model within stochastic DEA. The deterministic equivalent of this stochastic model is transformed into a nonlinear and then to a quadratic program. The objective function value and also the weighted output-input ratio, determined by using the optimal solution of the developed model, is used to evaluate DMUs. Two real data of the Chinese textile industry and Iranian provincial gas companies are used to assess the performance of the developed approach.

Online publication date: Tue, 26-Jul-2022

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