摘要
区间参数多目标优化问题是普遍存在且非常重要的。目前直接求解该类问题的进化优化方法非常少,且已有方法的目的是找到收敛性好且分布均匀的Pareto最优解集。为得到符合决策者偏好的最满意解,本文综述3种基于偏好的区间多目标进化算法,并将其应用于特定环境下机器人路径规划问题,比较3种算法的性能。研究结果可丰富特定环境下机器人路径规划的求解方法,提高机器人路径优化效果。
Interval multi-objective optimization problems are very popular and important.There exist few evolutionary optimization methods for directly solving them,and these existing methods aim at finding a set of well-converged and evenly-distributed Pareto-optimal solutions.Three preference-based interval multi-objective evolutionary algorithms are surveyed to obtain the most preferred solution fitted the decision maker＇s preferences.Additionally,the above algorithms are applied in robot path planning problems under a special environment,and are compared about their performance.The research enriches the methods of solving robot path planning problems under a special environment,and improves the optimization performance of the problems.
出处
《计算机与现代化》
2012年第11期43-46,共4页
Computer and Modernization
基金
淮海工学院自然科学基金资助项目(2010150037)
关键词
进化算法
多目标优化
区间
偏好
机器人
路径规划
evolutionary algorithm
multi-objective optimization
interval
preference
robot
path planning
