连续蚁群算法在水稻灌溉制度优化中的应用

    Application of ant colony algorithm based continuous space in optimizing irrigation regime of rice

    • 摘要: 为构建一种新的连续蚁群遗传算法,将优化连续空间变量的蚁群算法与实码加速遗传算法耦合,用蚁群算法将解空间分解成若干子空间,使解的范围均匀而广泛,为找到全局最优解奠定良好基础,且信息素的不断正反馈使问题向着更优解的方向逼近。综合二者的各自特点,通过对查哈阳灌区2006年水稻灌溉制度的优化,检验了该模型不但应用简便,且求解结果精度高、速度快,同时它的出现为制定合理的灌溉制度、提高水利用率提供科学依据,为优化领域提供新思路。

       

      Abstract: Putting forward a new ant colony algorithm in the continuous space optimization problems-real coding, coupling ant colony algorithm for optimizing continuous variables and real coding based on accelerating genetic algorithm, and dividing solution domain into some subspaces with ACA, solutions are dispersed widely and the optimal solution for the principle of pheromone positive feedback can be find easily. Using the advantages of the two algorithms, through optimizing irrigation regime of rice in Chahayang irrigation district in 2006, the results show that the new method is convenient and accurate, the model can provide scientific basis for making a reasonable irrigation schedule and improving water efficiency, and may give optimization field a new thought.

       

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