带自适应感知能力的粒子群优化算法

提出一种求解约束优化问题的改进粒子群优化算法。它利用可行性判断规则处理约束条件，更新个体最优解和全局最优解。通过为粒子赋予自适应感知能力，算法能较好地平衡全局和局部搜索，且有能力跳出局部极值，防止早熟。边界附近粒子的感知结果被用来修正其飞行速度以加强算法对约束边界的搜索。实验结果表明，新算法收敛速度快,寻优能力强，能很好地求解约束优化问题。

Perceptive particle swarm optimization algorithm for constrained optimization problems

A new Particle Swarm Optimization(PSO) algorithm was proposed to solve the constrained optimization problems.A feasibility-based rule handled constraints to update the individual optimal solutions and the global optimal solutions.Adaptive perceptive ability of particles can balance the global search and the local search.This ability can also help to avoid prematurity.The velocity of particle around the boundary was revised by the results of perceiving to enhance the search around the boundary.The simulation...