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高效的区间Pareto支配比较对于提高区间多目标进化优化算法性能至关重要.针对现有的区间多目标进化优化采用单一区间数比较的不足,提出基于混合比较策略的区间多目标进化优化算法.深入分析区间数μ比较和可能度P比较策略的优劣,提出融合这两种方法的混合比较策略和基于该混合策略的NSGA-II算法.该算法在典型多目标区间函数和含区间不确定性的煤矿井下射频识别阅读器布局中的应用,验证了所提出的混合区间比较策略的有效性.
Efficient interval Pareto domination comparison is crucial to improve the performance of interval multi-objective evolutionary optimization algorithm.According to the existing multi-objective evolutionary optimization of multi-objective optimization, a multi-objective interval optimization method based on hybrid comparison is proposed. This paper proposes a hybrid comparison strategy that combines these two methods and a NSGA-II algorithm based on this hybrid strategy, which is based on the analysis of the number of intervals μ and the probability P comparison strategy.The proposed algorithm is based on the typical multi-objective interval function and interval uncertainty The application of the hybrid interval identification strategy in coal mines verified the effectiveness of the proposed hybrid interval comparison strategy.