Hybrid particle swarm optimization for multiobjective resource allocation

作     者：Yi Yang Li Xiaoxing Gu Chunqin 

作者机构：Computer Science Dept. Sun Yat-sen Univ. Guangzhou 510275 P. R. China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2008年第19卷第5期

页      面：959-964页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：the National Natural Science Foundation of China (60573159) 

主　　题：resource allocation multiobjective optimization improved particle swarm optimization. 

摘      要：Resource allocation （RA） is the problem of allocating resources among various artifacts or business units to meet one or more expected goals, such a.s maximizing the profits, minimizing the costs, or achieving the best qualities. A complex multiobjective RA is addressed, and a multiobjective mathematical model is used to find solutions efficiently. Then, all improved particie swarm algorithm （mO_PSO） is proposed combined with a new particle diversity controller policies and dissipation operation. Meanwhile, a modified Pareto methods used in PSO to deal with multiobjectives optimization is presented. The effectiveness of the provided algorithm is validated by its application to some illustrative example dealing with multiobjective RA problems and with the comparative experiment with other algorithm.