摘要
主要针对离散型数学模型的优化问题,分析使用遗传和蚁群算法的优缺点,并克服遗传算法、蚁群算法各自的局限性,发挥其优势,通过遗传-蚁群融合算法进行优化计算。在研究过程中,采用C#语言实现融合算法,并定义标准输入和输出结构。利用油田措施优化应用案例进行了对比实验验证,结果表明,融合算法能有效地发挥遗传、蚁群算法的优点,运算速度及求解效率均较理想。
Analyzes the advantages and disadvantages of genetic algorithm and ant colony algorithm, targets to discrete optimization problems, and overcomes their own limitations, brings the strength by combining them together. Uses C# language to implement this algorithm, and defines the standard input and output structures. Practices have tested and verified this algorithm in oil field related projects, the result shows that this algorithm can perform very well both in speed and efficiency.
出处
《现代计算机》
2013年第22期24-27,共4页
Modern Computer
关键词
遗传算法
蚁群算法
遗传-蚁群融合算法
C#
Genetic Algorithms
Ant Colony Algorithm
Combination Algorithm of Genetic and Ant Colony
C#
