基于改进蚁群算法的四杆机构优化设计

在机构优化设计中，为了避免基本蚁群算法容易出现停滞现象、收敛速度慢的缺陷，将遗传算法和蚁群算法结合起来，在蚁群算法的每一次迭代中，首先根据信息量选择解分量的初值，然后使用变异操作来确定解的值。针对机构运动轨迹能够最佳逼近某一给定运动规律，且机构约束较多，采用改进蚁群算法对其进行优化计算。证明改进蚁群算法应用于机械优化计算切实可行。

Optimization Design of Four Bar Mechanism Based on the Improved Ant Colony Algorithm

In order to avoid the shortcomings of the basic ant colony algorithm, such as appearing stagnation behavior, making convergence speed slowly and the like. In this paper the ant algorithm and the genetic algorit.hm are considered together. In each iteration of the ant colony algorithm, the initial values of the components of the solution are selected by the trial information at first. Then the exact solution is determined by the operations of mutation. It is used in the optimum design of four bar mechanism with given motion regulation and multi-constrains. The results show that the two algorithms are practical and the algorithm is more effective. The paper gives a new way for solving similar complicated mechanical optimization problems.