An optimal order quantity model for multi-products with uncertain arrival time

Based on the analysis and summary of the features of supply chain components as well as the sales company itself, the problem of allocating order quantity of multi-products in several periods with an uncertain arrival time is investigated for a sales company. A concept of random fuzzy arrival rate is proposed to describe the uncertainty of the arrival time effectively, and the customer satisfaction is guaranteed by a transfer strategy. Considering all the factors including order costs, inventory costs, and transfer costs, a random fuzzy optimal order quantity model of multi-products with uncertain arrival time is established to minimize the total costs with constraints of purchase quantity, inventory capacity and current capitals based on the random fuzzy theory in uncertain theory. The multi-products optimal order quantity model with a random fuzzy variable is transferred into a random fuzzy expected value model to calculate the solutions. Genetic Algorithm is employed to solve the problem according to the characteristics and complexity of the solution. Simulation experiments were conducted using practical data of a sales company, and the results verified the effectiveness and efficiency of the proposed model and the solving algorithm.