This paper studies a multi-item dynamic lot size problem for perishable products where stock deterioration rates and inventory costs are age-dependent. We explore structural properties in an optimal solution under two cost structures and develop a dynamic programming algorithm to solve the problem in polynomial time when the number of products is fixed. We establish forecast horizon results that can help the operation manager to decide the precise forecast horizon in a rolling decision-making process. Finally, based on a detailed test bed of instance, we obtain useful managerial insights on the impact of deterioration rate and lifetime of products on the length of forecast horizon.
We consider the dynamic lot size problem for perishable inventory under minimum order quantities. The stock deterioration rates and inventory costs depend on both the age of the stocks and their periods of order. Based on two structural properties of the optimal solution, we develop a dynamic programming algorithm to solve the problem without backlogging. We also extend the model by considering backlogging. By establishing the regeneration set, we give a sufficient condition for obtaining forecast horizon under without and with backlogging. Finally, based on a detailed test bed of instance, we obtain useful managerial insights on the impact of minimum order quantities and perishability of product and the costs on the length of forecast horizon.
Abstract. This study explains and demonstrates whether China has the capability to avoid the Middle Income Trap. The 19th National Congress of CPC report points out: by 2035, China will become an international leader in innovation. At present, China is in the juncture of changing the mode of development, optimizing the economic structure and transforming the growth momentum. The juncture means that it is possible to be stagnation or retrogression of national economy as the national ability of innovation is insufficient, then sticking in the middle-income trap (MIC) for a long time. In this paper, we used the TFP to prove that the input-output ratio of different regions of China, with the per capita GDP and carbon emissions are fitting again, dividing China into optimized zones and non-optimized zones. It can be seen from the results that the optimized zones have achieved the peak of carbon emission and had relative advantages in green innovation. However, if China wants to achieve her overall carbon emissions and get out of the middle income trap, she must optimize the development zones to spillover technologies and talents.
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