| 多种群协同进化算法在经济调度中的应用 |
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| 引用本文： | 吴应斌,孟宪明,陈瀚宁.多种群协同进化算法在经济调度中的应用[J].计算机工程,2010,36(22):173-174. |
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| 作者姓名： | 吴应斌 孟宪明 陈瀚宁 |
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| 作者单位： | (1. 辽宁广播电视大学教务处，沈阳110034；2. 中国科学院沈阳自动化研究所工业信息学重点实验室，沈阳 110016) |
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| 基金项目： | 国家"863"计划基金资助项目 |
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| 摘 要： | 为解决同时考虑环保要求、发电费用等多个目标的经济调度问题，基于生态系统中不同物种间的互利共生现象，提出一种多种群共生进化优化(SMSO)算法。对一个30节点IEEE系统进行计算，结果显示SMSO算法在获得最优Pareto解集、降低计算复杂度、提高收敛效率等方面具有较大的优越性。
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| 关 键 词： | 粒子群优化算法 共生 电力调度 |
Application of Multi-Species Coevolutionary Algorithm in Economic Dispatch |
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| WU Ying-bin,MENG Xian-ming,CHEN Han-ning.Application of Multi-Species Coevolutionary Algorithm in Economic Dispatch[J].Computer Engineering,2010,36(22):173-174. |
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| Authors: | WU Ying-bin MENG Xian-ming CHEN Han-ning |
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| Affiliation: | (1. Teaching Affairs Office, Liaoning Radio and TV University, Shenyang 110034, China; 2. Key Laboratory of Industrial Informatics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China) |
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| Abstract: | A symbiotic multi-swarm coevolutionary optimization algorithm named SMSO(Symbiotic Multi-Species Optimization) is presented for multi-objective economic power dispatch problems such as environment protection and power cost. The effectiveness of SMSO is demonstrated with the IEEE 30-bus system, and the results demonstrate the better Pareto front, the computation complexity reduction and the convergence efficiency improvement of the proposed algorithm. |
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| Keywords: | Particle Swarm Optimization(PSO) algorithm symbiosis power dispatch |
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