Developing a Chance-Constrained Free Disposable Hull Model for Selecting Third-Party Reverse Logistics Providers

摘要

Demand of third-party reverse logistics (3PL) provider becomes an increasingly significant topic for corporations looking for enhanced customer service and cost reduction. To select the best 3PL providers in the presence of stochastic data, this paper proposes an innovative approach which is based on free disposable hull (FDH). FDH model is one of the classical models in data envelopment analysis (DEA). In many real world applications, data are often stochastic. A successful approach to address uncertainty in data is to replace deterministic data via random variables, leading to chance-constrained DEA. In this paper, a chance-constrained FDH (CCFDH) model is developed and also its deterministic equivalent which is a nonlinear program is derived. Furthermore, it is shown that the deterministic equivalent of the CCFDH model can be converted into a quadratic program. In addition, sensitivity analysis of the CCFDH model is discussed with respect to changes on parameters. Finally, a numerical example demonstrates the application of the proposed model in the field of 3PL provider selection.