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The need for air conditioners (ACs) is increasing every year, particularly in the Kingdom of Saudi Arabia (KSA). The annual sales of ACs clearly indicated either buying new conditioning systems or replacing existing ACs. When air conditioners are replaced for any reason, a large number of used air conditioners are available, which leads to the necessity of remanufacturing these ACs for economic and environmental purposes. The current research focuses on investigating the collection system of used window ACs as a part of the reverse logistics of remanufacturing window ACs under the uncertainty of demand and production rate. To optimize the average inventory and fulfill the need of the ACs remanufacturing unit, this current research explained many operations in the collection system and their relationship to the remanufacturing unit. These objectives were investigated using a combination of simulation, mathematical, and optimization techniques. After developing the model using Arena software, the simulation model for the initial solution was run. The theoretical and mathematical concepts of inventory have been exploited to find an initial solution for the objectives under investigation. The Optquest tool was used for the simulation model of the initial solution to improve the iterative search technique. Finally, a sensitivity analysis was carried out to determine each input parameter’s magnitude and individual impact on the results. The findings suggest that simulation and optimization strategies are effective in improving average inventory and lost demand. As a result, the average inventory has been reduced significantly.

Collection System of Air Conditioners Remanufacturing: Development and Optimization under Probabilistic Uncertainty