Inverse DEA under inter-temporal dependence using multiple-objective programming

• Modeling inverse DEA under inter-temporal dependence assumption.
• Input-estimation and output-estimation under inter-temporal dependence.
• Introducing a new optimality notion for MOP, periodic weak Pareto optimality.
• Using periodic weak Pareto optimality in inverse DEA.
• Characterizing periodic weak Pareto solutions.

This paper deals with the inverse Data Envelopment Analysis (DEA) under inter-temporal dependence assumption. Both problems, input-estimation and output-estimation, are investigated. Necessary and sufficient conditions for input/output estimation are established utilizing Pareto and weak Pareto solutions of linear multiple-objective programming problems. Furthermore, in this paper we introduce a new optimality notion for multiple-objective programming problems, periodic weak Pareto optimality. These solutions are used in inverse DEA, and it is shown that these can be characterized by a simple modification in weighted sum scalarization tool.