Presenting a New Mathematical Programming Model for the Storage Locations Assignment in the Automated Storage and Retrieval System Under the Conditions of Demand Uncertainty and Solving it with a Robust Optimization Method; (Case Study: Iran Khodro Warehouse)

In this research, based on the conditions and limitations of Iran Khodro's automatic warehouse, a non-linear three-objective mathematical programming model is proposed. Since the demand for warehouse pallets has high uncertainty due to the fluctuation of customer demand, the mathematical model has been based on the P-Robustness method to deal with the effect of changing demand on the optimal solution, and then the problem is converted to a single-objective mathematical model. It turns out that two meta-heuristic algorithms e.g., genetic algorithm and simulated annealing algorithm have been used to solve it in large scales. To check the performance of the two algorithms, the T-test in Minitab software was used to compare the average values of the objective function from 15 times solving numerical problems in different dimensions. Introducing a new index for better allocation of pallets to storage locations in Iran Khodro's automatic warehouse has reduced the distance, time, energy, and costs of storage retrieval and handling, which due to the high turnover of parts in the warehouse, can be concluded that significant savings have been achieved