从生物进化角度将群体中的每只昆虫看成一个神经元,彼此之间通过随机、松散的连接组成一个神经网络:然后类似于人工神经网络模拟蚂蚁群体智能,提出了一个二元网络.由于采用二进制编码对单个蚂蚁的智能行为要求比较低,对应的存储空间相对较少,使得算法的效率有较大的提高.通过测试函数优化和多维0/1背包问题结果表明该算法具有较好的收敛速度和稳定性,非常好的求解结果.
Every insect is considered, from the viewpoint of biological evolution, to be a neural cell that constitutes a neural network in a casual and loose way of joint. Through simulating the ant swarm intelligence on the basis of human neural network, this paper advances a linear binary network. The binary code expects a low intelligence of each ant, and each path corresponds to a comparatively small storage space, thus considerably improving the efficiency of computation. The test of function optimization and multi-dimensional 0/1 Knapsack proves that the computation has a good speed of convergence, a high stability and a perfect solution.