عنوان مقاله [English]
In this paper, we consider a multi-product newsvendor problem with the possibility of bundling the products. Selling price for each product and bundle as well as their quantities to be ordered at the beginning of the period are decision variables in the model. The objective is to maximize expected revenue of the newsvendor by considering holding and shortage costs. We also assume that the products are cross-elastic and demand of each product or bundle is a stochastic function of its price and the price of other products. With the best of our knowledge, this is the first study that considers a newsvendor problem with multiple products and stochastic demand determining the inventory related decision and sales price for each product and bundle. The products can be grouped as bundles for sale, assuming that the price of each bundle is less than the sum of products prices existing in the bundle. Therefore, the products and bundles are available for customers at the same time. The solution approach is a two-stage algorithm based on Multi Directional Search and Nest Partitioning algorithm. The solution algorithm benefits from advantages of both methods simultaneously. At the first stage, it makes the solution space limited in order to search for better solutions in a limited space at stage 2. Since only one set of variables is obtained by solving the model every time, the solution accuracy increases while the algorithm runtime decreases. The developed solution algorithm is strictly in line with conditions of our problem. Detailed examples are provided. The numerical results show the reasonable performance of the algorithm. Sensitivity analysis is done to provide managerial insights and conditions under which bundling is profitable. The results indicate that by applying the bundling strategy to newsvendor problem in the case of complementary products, large-sized markets and more bundle price sensitivity are highly recommended. Finally, the future studies are proposed.