期刊
OPERATIONS RESEARCH
卷 68, 期 4, 页码 1063-1073出版社
INFORMS
DOI: 10.1287/opre.2019.1971
关键词
inventory; lost sales; random supply function; constant-order policy; lead time; penalty cost
资金
- Chinese University of Hong Kong (CUHK) Direct Grant [4057117]
- Hong Kong Research Grants Council (RGC) General Research Fund [CUHK14200718, CUHK14500215]
- National Natural Science Foundation of China [11771432, 11401566]
We consider an infinite-horizon lost-sales inventory model where the supply takes positive lead times and is a random function of the order quantity (e.g., random yield/capacity). The optimal policy for this model is computationally intractable, and no heuristic has been proposed in the literature. In this paper, we focus on a simple class of constant-order policies (COPs) that place the same order in every period regardless of the system state. Under some assumptions on the random supply function, we prove that the best COP is asymptotically optimal with large lead times, and the optimality gap converges to zero exponentially fast in the lead time. We also prove that if the mean supply capacity is less than the mean demand, then the best COP is also asymptotically optimal with large penalty costs; otherwise, the long-run average cost of the best COP asymptotically increases at the rate of the square root of the penalty cost. Further, we construct a simple heuristic COP and show that it performs very close to the best COP. Finally, we provide a numerical study to derive further insights into the performance of the best COP.
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