Design and planning of closed loop supply chains: a risk averse multi-stage stochastic approach

Abstract

This paper presents a comprehensive risk-averse multistage model for dealing with the design and planning problem of a closed-loop supply chain (CLSC) considering adjustments in the supply chain structure during the planning horizon as well as uncertainty in supply and customer demands. The stochastic approach addresses a problem of a generic multiperiod multiproduct CLSC with a general network structure of ten types of entities, risk-averse objectives associated with both costs and revenues, a flexible network structure, transport capacity, salvage grade of returned products, CO2 emissions of the transport system, as well as minimum and maximum storage and processing capacity limits for network entities. A key aspect of the proposed work is to cope with a multiobjective function where the maximization of the expected profit is combined with the fundamental idea of risk management incorporated through the explicit trade-off between risk associated with costs and revenues. To the authors? knowledge, the joining of the considerations of risk management and aspects related to the opening/closing of entities during the planning horizon in a multistage stochastic context has not yet been considered. With the objective of achieving more reliable solutions, five objective functions that include risk-averse criteria are considered. A sensitivity analysis of the approach performance considering changes in the parameters associated with the risk metrics is conducted. Variations in the relevance of the risk quantification are carried out in order to show the trade-off between solution quality and handling of uncertainty.