摘要
针对电力市场的投资组合优化问题,采用多目标花授粉算法(MOFPA)构造Pareto最优解集,为发电商面临不同的交易做出选择。为避免多元化不足,增加一个目标以增强多元化,得到四目标的均值-方差-偏度(MVS-D)组合模型。与MOPSO和MOGAS进行比较,算例结果表明MOFPA能够得到的基于MVS-D优化模型较优的帕累托解,能为发电商提供更好的权衡解决方案,同时促进发电企业投资主体的多元化。
In view of solving the portfolio optimization problem for a power Generation Company(GenCo)faced with different trading choices,it uses the Multi-Objective Flower Pollination Algorithm(MOFPA)structural Pareto fronts set.To avoid under-diversification,an additional objective to enhance the diversification benefit is proposed alongside with the four original objectives of the Mean-Variance-Skewness(MVS-D)portfolio framework.Compared the simulation with MOPSO and MOGAS,the results show that MOFPA has made possible the inclusion of the optimization framework that produces Pareto fronts that also cover those based on the traditional MVS-D framework,thereby offering better trade-off solutions while promoting investment diversification benefits for power generation companies.
作者
贺兴时
张迷
任雪婷
HE Xingshi;ZHANG Mi;REN Xueting(School of Science, Xi’an Polytechnic University, Xi’an 710048, China)
出处
《计算机工程与应用》
CSCD
北大核心
2017年第17期234-240,共7页
Computer Engineering and Applications
基金
陕西省自然科学基础研究计划项目(No.2014JM1006)
陕西省自然软科学研究计划项目(No.2014KRM28-01)
陕西省教育厅专项科研计划项目(No.14JK1282)
关键词
花授粉算法
多目标优化
投资组合
帕累托解
flower pollination algorithm
multi-objective optimization
portfolio
pareto fronts
