Developing multi-objective mathematical model of sustainable multi-commodity, multi-level closed-loop supply chain network considering disruption risk under uncertainty

Nowadays, the issue of the difference in core competencies has turned into the main factor of competition in the market in most organizations. In line with their operational area, the companies make decisions to further strengthen some of their capabilities, capacities, and specializations. Thus, when an organization concentrates on its strengths and makes efforts for its sustainable development, a competitive advantage evolves in the market. In this regard, the present study proposes a Multi- Objective, Multi-Level, Multi-Commodity, and Multi-Period Closed-Loop Mathematical Model for production, distribution, location, and allocation of the products. The presented model particularly aims to minimize the environmental effects and the total supply chain costs, and to control the social impacts of the supply chain. The present study is mainly innovative in the sense that it considers the quality of the manufactured and transported products, various scenarios in the closed-loop logistics as uncertainty, the capacity of the distribution and production centers, and along with the current multi-commodity discussions, considers the sustainability and resilience in the supply chain, the environmental effects in the model and minimizing the amount of the CO2 emissions. The introduced model was solved in small and medium scales using the Epsilon Constraint approach and in large scales for the case study of Sunny Plast Industries by the Non-Dominated Sorting Genetic Algorithm- II (NSGA-II) approach. The results indicated that as the demand goes up, the costs rise. Costs increase is higher in the Boom Scenario than in the Bust Scenario. Also, with the rise in demands, the number of established centers increases. This increase is faster in the Boom case.