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首页> 外文会议>Italian Conference on Chemical and Process Engineering(ICheaP-6) vol.2; 20030608-11; Pisa(IT) >Computational Framework for Supply Chain Analysis
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Computational Framework for Supply Chain Analysis

机译：供应链分析的计算框架

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摘要

Managing supply chains is a challenging task, as is apparent when one considers the multiple interacting functions, the information required to represent them, and the uncertainties inherent to such a system. In certain supply chains, even managing the production function alone is difficult due to the complexity of combinatorial decision-making under uncertainty. To realistically represent such complex systems in as much detail as possible, a high-level architecture that combines discrete event simulation and optimization techniques is described. Its applicability to two systems, viz., a decentralized supply chain, and a large-scale production system under centralized control, is illustrated. In the former, supply chain entities use deterministic optimization tools to make decisions, and the system progresses over the planning horizon in uniform-time increments. In the latter, a single supply chain production entity implements the solution obtained from a deterministic scheduler in a discrete-event simulator to gauge the effects of uncertainty. While the first case seeks to analyze decentralized supply chain dynamics, the latter case addresses the difficult problem of optimizing safety stock levels at a plant. These two cases demonstrate that complex systems can be modelled to a satisfactory level of detail using the proposed framework.
机译：管理供应链是一项艰巨的任务，这很明显，当人们考虑多重相互作用的功能，代表这些功能的信息以及此类系统固有的不确定性时，这一点显而易见。在某些供应链中，由于不确定情况下组合决策的复杂性，即使仅管理生产功能也很困难。为了尽可能详细地现实地表示这种复杂的系统，描述了一种结合了离散事件模拟和优化技术的高级体系结构。说明了其对两个系统的适用性，即分散式供应链和集中控制下的大规模生产系统。在前者中，供应链实体使用确定性优化工具进行决策，并且系统以统一的时间增量在计划范围内前进。在后者中，单个供应链生产实体在离散事件模拟器中实施从确定性调度程序获得的解决方案，以评估不确定性的影响。第一种情况试图分析分散的供应链动态，而后一种情况则解决了优化工厂安全库存水平的难题。这两种情况表明，使用建议的框架可以将复杂的系统建模到令人满意的详细程度。

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