Developing a Robust Fuzzy Programming Approach for Closed Loop Supply Chain Design

Abstract

In recent decade, the increasing importance of economic benefits and environmental impacts of using scrapped products has encouraged to focus on the CLSC design. This paper considers the problem of CLSC network design under hybrid uncertain conditions, under which exist two sources of uncertainty for some parameters, thus require a strengthening of the robustness of the decision. The first source is that some uncertain parameters may be based on future scenarios. The second is that the values of these parameters in each scenario are usually as imprecise and can be specified by possibilistic variables. The fixed cost of opening manufacturing centers is assumed to be non-linear and dependent upon the capacity. Possibility theory is applied to choose such solution in such a problem and a robust fuzzy stochastic programming (RFSP) approach is proposed. The performance of the proposed RFSP model is also compared with that of mean model in term of the variability and mean cost of model.

Keywords

• fuzzy stochastic programming
• robust optimization
• non-linear model
• closed-loop supply chain