关键词: 几何约束求解, 人工蜂群算法, 粒子群优化, 优化算法

Abstract: Geometric constraint solving problem is the current hot issue of constraint solving techniques. The ultimate goal of geometric constraint solving is to determine the specific geometry of each coordinate position. The constraint equations of geometric constraint problem can be transformed into single target optimization model, so the constraint problem can be transformed into optimization problem. This paper uses an improved artificial bee colony algorithm (IABC) to solve geometric constraint problem. In the search phase, the IABC is through multidimensional searching towards optimal value instead of random one-dimensional searching of ABC, thereby enhancing the ability of local optimization, accelerating the convergence rate, eventually to find the global optimum. The experiments show that the improved artificial bee colony algorithm for solving geometric constraint problems has the advantages of high efficiency, fast convergence, high precision.

Key words: geometric constraint solving, artificial bee colony algorithm, particle swarm optimization, optimization algorithm