Deductive Sort and Climbing Sort: New Methods for Non-Dominated Sorting

被引:101
作者
McClymont, Kent [1 ]
Keedwell, Ed [1 ]
机构
[1] Univ Exeter, Coll Engn Math & Phys Sci, Exeter EX4 4QJ, Devon, England
基金
英国工程与自然科学研究理事会;
关键词
Non-dominated sorting; Pareto optimal; Pareto front; genetic algorithms; evolution strategies; MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS;
D O I
10.1162/EVCO_a_00041
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
In recent years an increasing number of real-world many-dimensional optimisation problems have been identified across the spectrum of research fields. Many popular evolutionary algorithms use non-dominance as a measure for selecting solutions for future generations. The process of sorting populations into non-dominated fronts is usually the controlling order of computational complexity and can be expensive for large populations or for a high number of objectives. This paper presents two novel methods for non-dominated sorting: deductive sort and climbing sort. The two new methods are compared to the fast non-dominated sort of NSGA-II and the non-dominated rank sort of the omni-optimizer. The results demonstrate the improved efficiencies of the deductive sort and the reductions in comparisons that can be made when applying inferred dominance relationships defined in this paper.
引用
收藏
页码:1 / 26
页数:26
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