A Python package for multi-stage stochastic programming
A Python package for multi-stage stochastic programming
复制标题
用于多阶段随机编程的 Python 包
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
H. Milton
中科院分区：
文献类型：
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作者：
L. Ding;Shabbir Ahmed;A. Shapiro;H. Milton
本文提出了一个求解多阶段随机线性规划（MSLP）和多阶段随机整数规划（MS-IP）的Python包。实现了基于广义公式和随机对偶动态（整数）规划（SDDP/SDDiP）方法的算法。该软件包是综合友好的，并具有许多在竞争软件包中不可用的功能。特别是，这个包处理了以前可用的软件包对底层数据过程施加的一些限制。作为包的应用，讨论了三个大规模的现实问题-电力系统规划，投资组合优化，航空公司收益管理。
This paper presents a Python package to solve multi-stage stochastic linear programs (MSLP) and multi-stage stochastic integer programs (MS-IP). Algorithms based on an extensive formulation and Stochastic Dual Dynamic (Integer) Programming (SDDP/SDDiP) method are implemented. The package is synthetically friendly and has a number of features which are not available in the competing software packages. In particular, the package deals with some of the restrictions on the underlying data process imposed by the previously available software packages. As an application of the package, three large-scale real-world problems - power system planning, portfolio optimization, airline revenue management, are discussed.
影响因子：
2.7
作者：
Jikai Zou;Shabbir Ahmed;X. Sun
通讯作者：
Jikai Zou;Shabbir Ahmed;X. Sun