在线时间序列搜索的风险补偿模型

doi:10.15960/j.cnki.issn.1007-6093.2019.03.009

运筹学学报 ›› 2019, Vol. 23 ›› Issue (3): 126-134.doi: 10.15960/j.cnki.issn.1007-6093.2019.03.009

在线时间序列搜索的风险补偿模型

张文明¹, 程永席^2,3,*, 茹少峰¹

1. 西北大学经济与管理学院, 西安 710127;
2. 西安交通大学管理学院, 西安 710049;
3. 机械制造系统工程国家重点实验室, 西安 710049

收稿日期:2019-03-11 发布日期:2019-09-09
通讯作者: 程永席 E-mail:chengyx@mail.xjtu.edu.cn
基金资助:
陕西省教育厅专项科研计划项目（No.17JK0785），国家自然科学基金（No.11771346）

The risk-reward model of the online time series search problem

ZHANG Wenming¹, CHENG Yongxi^2,3,*, RU Shaofeng¹

1. School ofEconomics & Management, Northwest University, Xi'an 710127, China;
2. School of Management, Xi'an Jiaotong University, Xi'an 710049, China;
3. StateKey Lab for Manufacturing Systems Engineering, Xi'an 710049, China

Received:2019-03-11 Published:2019-09-09

摘要/Abstract

摘要： 对于在线时间序列搜索问题，在假设对未来信息有一定的预期下，提出了在线时间序列搜索的风险补偿模型，进一步研究了模型的求解，给出了模型的一个最优策略，并通过数值计算讨论了最优策略的补偿函数随参数变化规律.数值实验结果表明，随着风险容忍度的增大与预期区间下限的增大，补偿函数均增大且趋于收敛；随着预期概率的增大与预期区间上限的减少，补偿函数分别增大.研究结果丰富了在线时间序列搜索的理论且具有实际应用价值.

关键词: 在线问题, 时间序列搜索, 风险补偿, 概率预期

Abstract: The risk-reward model of the time series search problem is promoted under the assumption that the future can be partially forecasted, where an optimal strategy is presented. Moreover, the variations of the reward function with the parameters are studied by numerical computation, which show that the reward first increases and then is convergent as the risk tolerance and the lower limit of the expectation interval rise, respectively, and increase as the expectation probability rises and the upper limit of the expectation interval declines, respectively. The results enrich the theory of online time series search and are valuable in application.

Key words: online problem, time series search, risk-reward, probabilistic forecast

中图分类号:

TB114.1

张文明, 程永席, 茹少峰. 在线时间序列搜索的风险补偿模型[J]. 运筹学学报, 2019, 23(3): 126-134.

ZHANG Wenming, CHENG Yongxi, RU Shaofeng. The risk-reward model of the online time series search problem[J]. Operations Research Transactions, 2019, 23(3): 126-134.

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在线时间序列搜索的风险补偿模型

The risk-reward model of the online time series search problem

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