This paper concerns with modeling and design of an algorithm for the portfolio selection problems with fixed transaction costs and minimum transaction lots. A mean-variance model for the portfolio selection problem is...This paper concerns with modeling and design of an algorithm for the portfolio selection problems with fixed transaction costs and minimum transaction lots. A mean-variance model for the portfolio selection problem is proposed, and the model is formulated as a non-smooth and nonlinear integer programming problem with multiple objective functions. As it has been proven that finding a feasible solution to the problem only is already NP-hard, based on NSGA-II and genetic algorithm for numerical optimization of constrained problems (Genocop), a multi-objective genetic algorithm (MOGA) is designed to solve the model. Its features comprise integer encoding and corresponding operators, and special treatment of constraints conditions. It is illustrated via a numerical example that the genetic algorithm can efficiently solve portfolio selection models proposed in this paper. This approach offers promise for the portfolio problems in practice.展开更多
Because of the anonymity and openness of E-commerce, the on-line transaction and the selection of network resources meet new challenges. For this reason, a trust domain-based multi-agent model for network resource sel...Because of the anonymity and openness of E-commerce, the on-line transaction and the selection of network resources meet new challenges. For this reason, a trust domain-based multi-agent model for network resource selection is presented. The model divides the network into numbers of trust domains and prevents the inconsistency of information maintained by different agents through the periodical communication among the agents. The model enables consumers to receive the response from the agents much quicker because the trust values of participators are evalUated and updated dynamically and timely after the completion of each transaction. In order to make users choose the best matching services and give users with trusted services, the model takes into account the similarity between services and the service providers' recognition to the services. Finally, the model illustrates the effectiveness and feasibility according to the experiment.展开更多
文摘This paper concerns with modeling and design of an algorithm for the portfolio selection problems with fixed transaction costs and minimum transaction lots. A mean-variance model for the portfolio selection problem is proposed, and the model is formulated as a non-smooth and nonlinear integer programming problem with multiple objective functions. As it has been proven that finding a feasible solution to the problem only is already NP-hard, based on NSGA-II and genetic algorithm for numerical optimization of constrained problems (Genocop), a multi-objective genetic algorithm (MOGA) is designed to solve the model. Its features comprise integer encoding and corresponding operators, and special treatment of constraints conditions. It is illustrated via a numerical example that the genetic algorithm can efficiently solve portfolio selection models proposed in this paper. This approach offers promise for the portfolio problems in practice.
基金Supported by the National Natural Science Foundation of China (No. 60873203 ), the Natural Science Foundation of Hebei Province (No F2008000646) and the Guidance Program of the Department of Science and Technology in Hebei Province (No. 72135192).
文摘Because of the anonymity and openness of E-commerce, the on-line transaction and the selection of network resources meet new challenges. For this reason, a trust domain-based multi-agent model for network resource selection is presented. The model divides the network into numbers of trust domains and prevents the inconsistency of information maintained by different agents through the periodical communication among the agents. The model enables consumers to receive the response from the agents much quicker because the trust values of participators are evalUated and updated dynamically and timely after the completion of each transaction. In order to make users choose the best matching services and give users with trusted services, the model takes into account the similarity between services and the service providers' recognition to the services. Finally, the model illustrates the effectiveness and feasibility according to the experiment.