In this project, we will study the lotsizing problem with remanufacturing (LSPR), under the stochastic programming and robust stochastic programming viewpoint. Basically, the LSPR is an extension of the classical lotsizing problem in which a fixed amount of returned products enters the system. The objective of the problem is to determine a production plan to take into account the possibility of remanufacturing these returned products to fulfill the demands. However, there are some characteristics of the remanufacturing processes that become them challenging in the production planning, like the uncertainties related to the returned rate of the products and the processing and setup time of the remanufacture operations. Ignoring these uncertainties can lead to unrealistic models and/or inaccurate solutions. Thus, the main objective of this project is to propose optimization models to deal with uncertainty issues that affect the production planning in industrial settings with remanufacturing processes. As a methodology to handle data uncertainty, we propose the classical stochastic programming approach and the robust stochastic version to design solutions less sensitive to changes in the scenarios. The deterministic and stochastic models will be coded in GAMS language and solved by CPLEX 12 solver. This project is related to Projeto Temático FAPESP (Process 2010/10133-0), recently approved.Keywords: lostising problem; remanufacturing; stochastic programming; robust stochastic programming.
News published in Agência FAPESP Newsletter about the scholarship: