This paper deals with a multiperiod portfolio selection problem in an uncertain investment environment, in which the returns of securities are assumed to be uncertain variables and determined by experts' subjective evaluation. Based on uncertain theory, we present a novel multiperiod multiobjective mean-variance-skewness model by considering multiple realistic investment constraints such as transaction cost, bounds on holdings, cardinality, etc. For the proposed solution, we first apply a weighted max-min fuzzy goal programming approach to convert the proposed multiobjective programming model into a single-objective one. After that, we design a novel hybrid of an imperialist competitive algorithm (ICA) and a firefly algorithm (FA), termed ICA-FA, to solve it. Finally, we provide a numerical example to demonstrate the effectiveness of the proposed model and corresponding algorithm.

中文翻译：

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基于多准则的多周期不确定投资组合优化模型的新型混合ICA-FA算法


本文研究的是不确定投资环境下的多期投资组合选择问题，其中证券的收益被假设为不确定变量，并由专家的主观评价决定。基于不确定性理论，我们通过考虑多种现实投资约束（例如交易成本、持有界限、基数等），提出了一种新颖的多周期多目标均值-方差-偏度模型。对于所提出的解决方案，我们首先应用加权最大最小模糊目标规划方法将所提出的多目标规划模型转换为单目标规划模型。之后，我们设计了一种帝国主义竞争算法（ICA）和萤火虫算法（FA）的新颖混合体（称为 ICA-FA）来解决该问题。最后，我们提供了一个数值例子来证明所提出的模型和相应算法的有效性。