Inventory Models With Multiply Order In A Finite Planning Horizon Under Trade Credit

Enterprise’s planning horizon is finite. In actual production, the enterprise generally adopts credit payment in order to stimulate demand. At the same time, enterprises also use multiple orders strategy so as to balance supply and demand, decrease inventory and reduce the risk of investment. Therefore, the study of inventory problem in the finite planning horizon under trade credit has the vital practical significance, the main contents of this thesis includes:(1) The inventory problem of multiple orders for the deteriorating product with a quality guarantee period in the product life cycle is studied. The demand characteristic of the product in the product life cycle is described by a special power function. Supposing that the deteriorating rate of the product is relative to the storage time, an inventory model is developed under trade credit. A search algorithm for the order strategy is designed, and the optimality of every search step is discussed. Several numerical examples are presented, and the sensitivity analysis of the main parameters is carried out.(2) The inventory problem of multiple orders for product with time-varying demand under trade credit is studied. Supposed that demand rate is a general function of time and trade credit depends on the order quantity, an inventory model of multiple orders for deteriorating product in finite planning horizons established. A search algorithm for the order strategy is given, and the optimality of every search step is proved. Numerical examples with different types of demand function are presented. Sensitivity analyses of the major parameters are presented.(3) The inventory problem with multiple order and allowing shortages under trade credit is studied. Supposing that shortages are partially backlogged, and the backlogging rate is a decreasing function of the waiting time, an inventory model in finite planning horizon is established. A search algorithm for the order strategy is given, and the optimality of every search step is proved. Numerical examples are presented, and the influence of the main parameters on the total profit is analyzed.