Development and Analysis of Robust and Efficient Algorithms for Large Scale Production/Distribution Systems

Simchi-Levi这笔赠款为大规模物流系统的分析提供资金。在这种系统中，由一组部件组装而成的成品在分发到零售网点之前可能会在不同的地点生产和储存。因此，物流系统包括供应商、制造商、仓库和零售点，以及在设施之间流动的原材料、在制品库存和成品。目标是在满足所有需求的同时，协调生产、路线和发货时间，以最大限度地减少包括制造、库存和运输在内的全系统成本。这项研究的重点是采用两种运输方式的物流系统：私人车队或少于卡车载重车的运输方式。在这两种情况下，研究的目标都是了解最优解的基本理论结构，并将其用于开发实用和高效的算法。如果成功，这项研究的结果将导致开发有效的新算法，这些算法独立于特定环境和数据的可变性。也就是说，这些算法是健壮的；它们旨在处理一般设置，而不是一组库问题。这些算法使基于优化的决策支持系统的实现成为可能，这些系统考虑了物流网络各个层次之间的相互作用，并利用了供应链中丰富的可用信息。

9732795Simchi-Levi This grant provides funding for the analysis of large scale logistics systems. In such systems, finished products, which are assembled from a set of components, may be produced and stored in various locations prior to their distribution to retail outlets. Thus, the logistics system includes suppliers, manufacturers, warehouses and retail outlets as well as raw materials, work-in-process inventory and finished products that flow between the facilities. The objective is to coordinate production, routing and timing of shipment so as to minimize system-wide cost, including manufacturing, inventory and transportation, while satisfying all demands. The focus in this research is on logistics systems that employ two types of transportation modes; a private fleet, or Less Than Truck Load carriers. In both cases, the goal of the research is to understand the underlying theoretical structure of optimal solutions and utilize it in the development of practical and efficient algorithms. If successful, the results of this research will lead to the development of new algorithms that are effective,independent of the specific environment and the variability of the data. That is, these algorithms are robust; they are designed to handle a general setting rather than a set of library problems. These algorithms make it possible to implement optimization based decision support systems that take into account the interaction between the various levels of the logistics network, and utilize the wealth of available information in the supply chain.