Humoral Immune Algorithm and Its Application to Portfolio Selection
体液免疫算法及其对证券组合投资分析的应用

A portfolio selection quadratic integer programming model with minimum transaction lots is developed through designing a new asymmetric risk measurement based on the generalized disappointment model proposed by Jia and Dyer.Further,associated with humoral immune theory,a novel and available humoral immune algorithm is proposed to solve the model.In the design of the algorithm,the key is to introduce an excellent antibody set-updating operator to collect and update the good solutions found from the search process,while establishing several kinds of immune operations being capable of improving diversity of population and strengthening the capability of global,local,and parallel search so that the algorithm can search the optimal solution from different directions.Practical application and numerically comparative results,illustrating the reasonability and availability of the model,show that the proposed algorithm with strongly global and local search capability can obtain rapidly the optimal investment decision-making scheme of the model.