Heuristic method on solving an inventory model for products with optional components under stochastic payment and budget constraints

In recent years, enterprises must manage the inventory of items produced by multiple components and the interactions among those items because of a growing emphasis on modularization and customization. In fact, a powerful and affordable information technology system can make the continuous review of inventory more convenient, efficient, and effective. Thus, a (Q, r) model is developed in this study to find the optimal lot size and reorder point for a multi-item inventory model with interactions between necessary and optional components. In order to accurately approximate the related costs, the service cost is introduced and defined in proportion to the service level. In addition, the service costs are incorporated with budget constraint because the firm’s strategy could influence the choice of service level. The proposed model is formulated as a nonlinear, discrete optimization problem and some known procedures are revised to solve this problem. The results are compared with other models and show that the revised procedure performs better than the N–R procedure leading to the important insights about inventory control policy. The results also reveal that the total amount allowed for the issued orders is paid at the time an order is received when the budget constraint is elastic.