基于带变异算子粒子群优化算法的约束布局优化研究

该文研究二维带平衡及不干涉约束的圆集在圆容器内的布局优化问题(如卫星舱布局),属于NP-Hard问题,难于求解．文章提出了带变异算子的PSO算法(PSO with Mutation Operator),在算法搜索的后期引入变异算子,使算法摆脱后期易于陷入局部极优点的束缚,同时又保持前期搜索速度快的特性．将改进后的算法应用于约束布局问题,建立了此类问题的粒子群算法,并进行了3个算例(其中一个为已知最优解的算例)的数值计算,验证了带变异算子PSO算法在约束布局问题上的可行性和有效性．

A Study on the Particle Swarm Optimization with Mutation Operator Constrained Layout Optimization

Taking the layout problem of satellite cabins as background, the authors studies the optimal layout problem of circle group in a circular container with performance constraints of equilibrium, which belong to NP-hard problem. This paper extends the heuristic method called "Particle Swarm Optimization"(PSO) to deal with the constrained layout optimization problem, proposes the particle presentation for this problem and compares the PSO with GA. By adding the mutation operator to the PSO algorithm in the later phase of convergence, the advanced algorithm can not only escape from the local minimum's basin of attraction of the later phase, but also maintain the characteristic of fast speed in the early convergence phase. The experimental results indicate that the Mutation PSO is a more effective method for constrained optimal layout problem.