Multi-objective stochastic multi-site supply chain planning under demand uncertainty considering downside risk

- A multi-site supply chain planning problem under demand uncertainty is considered.
- A multi-objective stochastic model is developed for the considered problem.
- The proposed solution approach yields to a front of Pareto optimal robust solutions.
- A fuzzy decision making approach is applied to select the most preferred Pareto solution.

In this paper, a multi-period, multi-product, multi-site, multi-stage supply chain planning problem under demand uncertainty is considered. The problem is formulated as a two-stage stochastic linear programming model. In order to generate a robust supply chain planning solution, the downside risk is incorporated into the objective functions of the stochastic programming model as a risk measure. So, the proposed multi-objective stochastic model aims to simultaneously minimize the expected total cost, to minimize the lost customer demand level and to minimize the downside risk. The proposed solution approach yields to a front of Pareto optimal robust solutions. A fuzzy decision making approach is applied to select the most preferred solution among the Pareto optimal robust solutions. A numerical example from a real textile and apparel industry is addressed in order to illustrate the robustness of the supply chain network planning solutions and the effectiveness of the solution approach.