摘要
实际工程优化过程中,对于多个目标的优化与求解最优值是值得研究的一个问题。文章基于粒子群算法研究多目标优化问题,实现二维多目标搜索,运用粒子群多目标求解模型迭代实现动态多目标搜索,最终得到非劣解在目标空间中的分布,构成了Pareto面,得到非劣解集,在实际问题中,提供最优解的备选,为工程实践优化和筛选最优解问题提供参考依据。
In the process of actual engineering optimization, it is a problem to optimize and solve the optimal value of multiple targets. This paper based on multi-objective particle swarm optimization algorithm to realize two dimensional problem of multi-objective search, using multi-objective particle swarm model iterative dynamic multi-objective search, finally get the Pareto distribution in the objective space, a Pareto surface, get the non dominated solutions in practical problems, to provide the best alternative solution for engineering practice, and to provide reference for the optimization of optimal solutions.
出处
《信息通信》
2018年第2期77-79,共3页
Information & Communications
基金
国家自然科学基金(2015BAK38B00)
关键词
粒子群
多目标
螺旋
迭代
非劣解
Particle swarm optimization
multiple target
Spiral
Iteration
Noninferior solution
