论文标题
使用模块化技术缓解投资风险
Mitigating Investment Risk Using Modular Technologies
论文作者
论文摘要
我们研究由模块化处理技术提供的后勤投资灵活性，以减轻风险。具体而言，我们提出了一种多阶段随机编程公式，该公式决定了减轻需求不确定性的最佳容量扩展计划。该配方说明了小型/大型单位之间的多产品依赖性以及预期利润和风险之间的权衡。该配方使用累积风险措施来避免传统的，每个阶段风险最小化配方的时间段落问题，我们认为这种方法与诸如净现值等典型的投资指标更兼容。提出了不同复杂性的案例研究，以说明这些发展。我们的研究表明，柔性环境的帕累托前沿（允许小型单元的部署）主导着不灵活的环境的帕累托前沿（仅允许部署大型单元）。值得注意的是，尽管大型加工单元的规模经济带来的好处，但这种主导地位还是普遍的。
We study logistical investment flexibility provided by modular processing technologies for mitigating risk. Specifically, we propose a multi-stage stochastic programming formulation that determines optimal capacity expansion plans that mitigate demand uncertainty. The formulation accounts for multi-product dependencies between small/large units and for trade-offs between expected profit and risk. The formulation uses a cumulative risk measure to avoid timeconsistency issues of traditional, per-stage risk-minimization formulations and we argue that this approach is more compatible with typical investment metrics such as the net present value. Case studies of different complexity are presented to illustrate the developments. Our studies reveal that the Pareto frontier of a flexible setting (allowing for deployment of small units) dominates the Pareto frontier of an inflexible setting (allowing only for deployment of large units). Notably, this dominance is prevalent despite benefits arising from economies of scale of large processing units.
