Optimization of Modular Production Networks Considering Demand Uncertainties
Optimization of Modular Production Networks Considering Demand Uncertainties
复制标题
考虑需求不确定性的模块化生产网络优化
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
B. Werners
中科院分区：
文献类型：
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作者：
Tristan Becker;Pascal Lutter;S. Lier;B. Werners
在此过程中，行业市场面临着新的挑战：在产品生命周期变得越来越短的同时，产品的差异化也在增加。这导致了产品需求在时间和地点上的变化和不确定。作为反应，研究重点转向模块化生产，这使得生产网络更加灵活。利用小型工厂，生产地点可以直接靠近资源或客户。为了应对短期需求变化，可以通过在不同位置之间移动模块单元或向上编号来进行能力修改。为了从模块化生产的灵活性中获益，网络结构要求在每个阶段都进行动态适应。随后，一旦客户需求实现，就必须确定所处置的生产能力和客户订单之间的最优匹配。这种决策情况对规划工具提出了新的挑战，因为网络配置的频繁调整必须基于不确定的需求进行计算。我们开发了随机和稳健的混合整数规划公式来对冲需求的不确定性。在计算研究中，根据调整后的真实世界数据集在运行时间和解决方案质量方面对新配方进行评估。
In the process industry markets are facing new challenges: while product life cycles are becoming shorter, the differentiation of products grows. This leads to varying and uncertain product demands in time and location. As a reaction, the research focus shifts to modular production, which allow for a more flexible production network. Using small-scale plants, production locations can be located in direct proximity to resources or customers. In response to short-term demand changes, capacity modifications can be made by shifting modular units between locations or numbering up. In order to benefit from the flexibility of modular production, the structure of the network requests dynamic adaptions in every period. Subsequently, once the customer demand realizes, an optimal match between disposed production capacities and customer orders has to be determined. This decision situation imposes new challenges on planning tools, since frequent adjustments of the network configuration have to be computed based on uncertain demand. We develop stochastic and robust mixed-integer programming formulations to hedge against demand uncertainty. In a computational study the novel formulations are evaluated based on adjusted real-world data sets in terms of runtime and solution quality.