合蜂群杂草算法及其在灌溉制度优化中的应用

J4 ›› 2014, Vol. 36 ›› Issue (09): 1728-1735.

合蜂群杂草算法及其在灌溉制度优化中的应用

龚亚星1，王联国1,2

(1.甘肃农业大学工学院，甘肃兰州 730070；2.甘肃农业大学信息科学技术学院，甘肃兰州 730070)

收稿日期:2013-04-07 修回日期:2013-05-29 出版日期:2014-09-25 发布日期:2014-09-25
基金资助:
国家自然科学基金资助项目（61063028）；甘肃省教育信息化发展战略研究资助项目（2011）

A hybrid algorithm of bee colony and invasive weed
optimization and its application in irrigation schedule optimization

GONG Yaxing1，WANG Lianguo1,2

(1.College of Engineering,Gansu Agricultural University,Lanzhou 730070;2.College of Information Science and Technology,Gansu Agricultural University,Lanzhou 730070,China)

Received:2013-04-07 Revised:2013-05-29 Online:2014-09-25 Published:2014-09-25

摘要/Abstract

摘要：

首先针对杂草算法容易早熟收敛的问题，将人工蜂群算法的寻优机制引入其中，提出了一种混合蜂群杂草算法。该算法对杂草种群中的每个个体利用采蜜蜂搜索方式进行变异，对群体最优个体利用跟随蜂搜索方式进行变异，用较优的变异结果替代原有个体，提高了算法的收敛精度。然后，通过对几个标准测试函数进行实验，验证了改进算法的优化性能。最后，将该算法应用到灌溉制度优化问题中，为制定灌溉水量分配方案提供了一种新的工具。

关键词: 群体智能, 杂草算法, 蜂群算法, 遗传算法, Jesen模型, 优化灌溉

Abstract:

Firstly, aiming at the premature convergence problem of Invasive Weed Optimization (IWO) algorithm,a hybrid algorithm of Bee Colony and Invasive Weed Optimization (BCIWO) is proposed by introducing the optimization mechanism of Artificial Bee Colony (ABC) algorithm. Every individual in the weed colony is mutated by employed bees’ search behavior and the global best individual is mutated by onlookers’ search method in this improved algorithm. The better result of mutation is used to replace the original individual.Those improve the convergence speed and the accuracy of IWO.Then the optimal performance of BCIWO is verified by test functions.Finally,the new algorithm is applied into the irrigation schedule optimization problem,thus providing a promising way to allocate irrigation water.

Key words: swarm intelligence;invasive weed optimization algorithm;artificial bee colony algorithm;genetic algorithm;Jesen model;optimized irrigation

龚亚星1，王联国1,2. 合蜂群杂草算法及其在灌溉制度优化中的应用[J]. J4, 2014, 36(09): 1728-1735.

GONG Yaxing1，WANG Lianguo1,2. A hybrid algorithm of bee colony and invasive weed
optimization and its application in irrigation schedule optimization [J]. J4, 2014, 36(09): 1728-1735.

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