Multi-horizon stochastic programming
Multi-horizon stochastic programming
复制标题
多视野随机规划
DOI：
--
复制
发表时间：
2014
影响因子：
0.9
通讯作者：
Marte Fodstad
中科院分区：
文献类型：
--
作者：
M. Kaut;Kjetil T. Midthun;A. Werner;A. Tomasgard;Lars Hellemo;Marte Fodstad
基础设施规划模型具有挑战性，因为它们结合了不同的时间尺度：虽然规划和建设基础设施涉及具有多年时间范围的战略决策，但需要一个运营时间尺度来正确了解基础设施的性能和盈利能力。此外，战略和业务层面通常都存在重大不确定性，这一点必须加以考虑。由于模型规模的指数增长，两个不同时间尺度上的不确定性的组合给问题的传统多阶段随机规划公式带来了问题。在本文中，我们提出了一种结合了两个时间尺度的问题的替代公式，使用了我们所称的多水平方法，并在一个程式化的优化模型上进行了说明。我们表明，与传统的公式相比，新的方法大大降低了模型的规模，并给出了两个来自能源规划的实际应用。
Infrastructure-planning models are challenging because of their combination of different time scales: while planning and building the infrastructure involves strategic decisions with time horizons of many years, one needs an operational time scale to get a proper picture of the infrastructure’s performance and profitability. In addition, both the strategic and operational levels are typically subject to significant uncertainty, which has to be taken into account. This combination of uncertainties on two different time scales creates problems for the traditional multistage stochastic-programming formulation of the problem due to the exponential growth in model size. In this paper, we present an alternative formulation of the problem that combines the two time scales, using what we call a multi-horizon approach, and illustrate it on a stylized optimization model. We show that the new approach drastically reduces the model size compared to the traditional formulation and present two real-life applications from energy planning.