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Authors:
杜宁清
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Information:
西安电子科技大学,西安
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Keywords:
evolutionary algorithm; multi-objective optimization; interval; preference; robot; path planning
进化算法; 多目标优化; 区间; 偏好; 机器人; 路径规划
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Abstract:
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 Paretooptimal 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.
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。
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DOI:
https://doi.org/10.35534/ami.0202006c
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Cite:
杜宁清.基于偏好的区间多目标进化算法的比较与应用[J].应用数学资讯,2020,2(2):35-44.