In this research, the clothing industry has been investigated as one of the oldest and most important manufacturing industries. With the expansion of global markets in the 21st century, the clothing industry plays an essential role in the global economy, so that the value of this industry has reached about three trillion dollars. However, major problems such as heavy dependence on raw material resources and the inability of many companies to sustainably supply these resources have caused the clothing industry to become one of the biggest environmental polluters. Considering these challenges, the current research deals with the design of a multi-level supply chain network for this industry. This chain includes suppliers of raw materials, production and distribution centers, as well as stores, and its main goal is to optimize production and distribution processes with a focus on managing environmental sustainability, social impacts, and reducing waste. Looking at previous research, the gap in an integrated model that simultaneously explains the issues of sustainability and uncertainty in the market, taking into account all levels of the supply chain as well as reverse logistics conditions, is clearly evident, and therefore, in this research, this research gap has become the source of innovation. The model presented in this research uses the mixed integer mathematical modeling approach, which has the ability to optimize decisions at different levels of the supply chain. In this model, the limitations and complexities related to production, distribution and fluctuations of demand markets have been carefully considered. In addition, in order to face the uncertainties in the real world, Bertsimas robust optimization method has been used. This method, taking into account unexpected changes in demand input parameters, provides optimal and reliable solutions that can maintain the stability and efficiency of the supply chain in different conditions. In the continuation of the research, a precise method was used to solve the optimization model and the obtained results were eva‎luated through numerical analysis. In the eva‎luation process, the epsilon limit method has also been used, which provides the possibility of examining several different goals in the model, and analyzes the triple functions of the goal two by two and shows the conflict of each one with the other. Using this method, the performance of the model has been analyzed on the Pareto frontier in order to identify solutions that establish an optimal balance between economic efficiency and environmental and social sustainability. Sensitivity analyzes on the uncertainty budget have shown that the model obtained through Bertsimas method is very cost-effective in terms of a stable approach and the ability to face uncertainties, and the use of this approach is recommended. The overall results of this research show that the designed model can effectively help improve the performance of the clothing supply chain and enable organizations to make optimal and sustainable decisions even in the face of unforeseen changes and conditions. In addition, the use of hybrid approaches such as robust optimization and sensitivity analysis allows organizations to better manage the risks and instabilities in the supply and production process and adopt sustainable and effective solutions.

رضا حجازي طاقانكي

عليرضا گلي

فرشته پرورش , حسين خسروشاهي