解决约束优化问题的一种改进PSO研究

为有效求解约束优化问题，提出一种改进粒子群算法（ICPSO）。该算法在处理约束时不引入惩罚因子，而是根据目标函数值和粒子违背约束奈件程度。并根据种群中介体的可行性，采用三种不同的交叉操作对粒子自身最优位置进行操作，同时对全局最优粒子采取变异操作以产生新的学习样本，引导种群的飞行，提升种群跳曲局部最优解的能力。最后，引入一种混合粒子速度更新策略，提升种群向最优解飞行的概率。标准测试函数的仿真结果表明ICPSO是可行的，有效的。

Research of Improved PSO for Solving Constrained Optimization Problems

In order to solve constraint optimization problems,an improved particle swarm optimizer was proposed for solving constrained optimization problem(ICPSO for short),which did not introduce penalty parameters to deal with constraints,but deal with constraints in terms of objective and the degree of the violation.In the process of search,the ICPSO algorithm searched the solution space by three different crossover methods based on population feasibility to crossover the best previous position of each particle(pb...