Robust aggregate production planning in a green supply chain under uncertainty considering reverse logistics: a case study

In response to the environmental problems in the world, organizations need to apply green indicators to gain competitive advantages. Moreover, manufacturers need to fulfill the demands in such a way as to generate a stable plan in the real world. In this paper, a robust optimization approach is developed to solve a multi-site, multi- period, multi-product aggregate production planning problem in a green supply chain considering potential collection and recycling centers under uncertainty. The specific number of collection and recycling centers among potential centers can be constructed to manufacture the second-class products. Some green principles such as waste management, greenhouse gas emissions related to transportation modes, and production methods are embedded in the model. The objective function sets out to minimize total losses of considered supply chain. Demand fluctuations and cost parameters are subject to the uncertainty. A set of discrete scenarios are employed to illustrate the uncertainties. The robust optimization approach is chosen to reduce the impacts of fluctuations of uncertain parameters concerning all possible scenarios in the future. A case study from an Iranian Wood and Paper Industries Company is studied to indicate the practicability of the proposed model. The computational results demonstrate the effectiveness and robustness of the model. The cost analysis is carried out to provide useful managerial insights. The total costs and the profit in collection and recycling system, is also analyzed to indicate its performance.