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多种群协同进化算法在经济调度中的应用 被引量：2

Application of Multi-Species Coevolutionary Algorithm in Economic Dispatch
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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。 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.
作者 吴应斌 孟宪明 陈瀚宁
机构地区 辽宁广播电视大学教务处 中国科学院沈阳自动化研究所工业信息学重点实验室
出处 《计算机工程》 CAS CSCD 北大核心 2010年第22期173-174,共2页 Computer Engineering
基金 国家"863"计划基金资助项目(2006AA04A124)
关键词 粒子群优化算法 共生 电力调度 Particle Swarm Optimization（PSO） algorithm symbiosis power dispatch
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献5

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二级参考文献12

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共引文献21

同被引文献31

  • 1周广通,尹义龙,郭文鹃,任春晓.基于协同训练的指纹图像分割算法[J].山东大学学报（工学版）,2009,39(1):22-26. 被引量：3
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计算机工程
2010年 第22期

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