基于冠军竞争的在线非平稳库存控制
On-line Non-stationary Inventory Control using Champion Competition
摘要：
通常采用的平稳需求假设不能真实反映波动需求，在实际应用中会削弱求解的有效性。考虑一类在线非平稳库存控制问题（ONICP），在该问题中，对需求不作任何具体的假设，允许需求的概率分布随时间变化并相互关联.非平稳需求的性质使静态（s，S）策略的最优性及其相应算法的适用性失效。ONICP成为计算棘手的使用一般的基于仿真的优化（SO）方法，特别是在一个在线的决策环境下，没有奢侈的时间和计算资源，以负担巨大的计算负担。我们开发了一种新的SO方法，称为“冠军竞争”（CC），它提供了一个不同的框架，并绕过了耗时的样本平均常规采用一般SO方法。另一种类型的最优解，称为“冠军解决方案”，追求在CC框架，这符合传统的最优性意义在一定条件下，并作为一个近最优解的一般情况下。在求解包括ONICP在内的一类SO问题时，CC可以将一般SO方法的复杂性降低几个数量级。一个多项式算法，被称为“更新循环算法”（RCA），进一步发展，以履行CC框架中的一个重要步骤，在解决这个ONICP。数值例子来证明与RCA嵌入的CC框架的性能。
英文摘要：
The commonly adopted assumption of stationary demands cannot actually reflect fluctuating demands and will weaken solution effectiveness in real practice. We consider an On-line Non-stationary Inventory Control Problem (ONICP), in which no specific assumption is imposed on demands and their probability distributions are allowed to vary over periods and correlate with each other. The nature of non-stationary demands disables the optimality of static (s,S) policies and the applicability of its corresponding algorithms. The ONICP becomes computationally intractable by using general Simulation-based Optimization (SO) methods, especially under an on-line decision-making environment with no luxury of time and computing resources to afford the huge computational burden. We develop a new SO method, termed "Champion Competition" (CC), which provides a different framework and bypasses the time-consuming sample average routine adopted in general SO methods. An alternate type of optimal solution, termed "Champion Solution", is pursued in the CC framework, which coincides the traditional optimality sense under certain conditions and serves as a near-optimal solution for general cases. The CC can reduce the complexity of general SO methods by orders of magnitude in solving a class of SO problems, including the ONICP. A polynomial algorithm, termed "Renewal Cycle Algorithm" (RCA), is further developed to fulfill an important procedure of the CC framework in solving this ONICP. Numerical examples are included to demonstrate the performance of the CC framework with the RCA embedded.
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