GOALI: Inventory Management in Assemble-to-Order Systems: Analysis, Policies, and Asymptotic Optimality

GOALI学术联络机会奖的目的是为按订单装配制造系统中的库存管理开发一个具有一般结构和参数值的优化框架。基本方法是利用随机规划将一个棘手的控制问题转化为一个更简单的可解优化问题。随机规划的最优解为长期平均期望总库存成本设定了一个可证明的下界，它将被用来启发一系列用于管理动态系统的库存控制策略。这些政策将通过扩散尺度上的渐近最优性标准进行检验。换句话说，当零部件提前期增加，从而使系统成本更高时，拟议的政策将使库存成本与其下限之间的百分比差异为零。还将通过数值实验、模拟和案例研究，包括与其他方法的比较和最不有利条件下的压力测试，对这些政策在不同参数区域的性能进行经验性评估。这项研究的结果将帮助制造企业实现显著的库存成本节约，从而提高广泛采用的按订单装配制造策略的效率。由于这些政策对交付期较长的系统特别有效，它们将缓解制造商与海外供应商之间长期运输延误对库存系统的负面影响，从而导致有利于外包的成本效益计算发生变化，这将有助于美国制造业的振兴。随机规划和渐近分析的组合使用也指出了库存管理优化的一种很有前途的新方法，这涉及到许多出了名的困难问题。

The objective of this Grant Opportunity for Academic Liaison with Industry (GOALI) award is to develop an optimization framework for inventory management in Assemble-to-Order manufacturing systems with general structures and parameter values. The basic approach is to employ a stochastic program to transform an intractable control problem into a much simpler solvable optimization problem. The optimal solution of the stochastic program, which sets a provable lower bound on the long-run average expected total inventory cost, will be used to inspire a family of inventory control policies for managing dynamic systems. These policies will be tested by the criterion of asymptotic optimality on the diffusion scale. In other words, when component lead times increase, thus making the system more costly, the proposed policies will drive the percentage difference between the inventory cost and its lower bound to zero. Performance of these policies in various parameter regions will also be evaluated empirically by numerical experiments, simulations, and case studies, including comparisons with other approaches and stress-tests under the least favorable conditions. Algorithms involving approximations will be developed to allow the approach to be implementable on an industrial scale.If successful, the results of this research will help manufacturing companies to achieve significant savings in inventory cost, thus improving the efficiency of the widely-adopted Assemble-to-Order manufacturing strategy. Because the policies are particularly effective for systems with long lead times, they will mitigate negative impacts on the inventory system of long transportation delays between manufacturers and their oversea suppliers and thus lead to changes in the cost-benefit calculation that favor insourcing, which will contribute to the US manufacturing sector's revitalization. The combined use of stochastic programs and asymptotic analysis also points to a promising new approach for inventory management optimization, which involves many notoriously hard problems.