A Generator for Multiobjective Test Problems With Difficult-to-Approximate Pareto Front Boundaries
A Generator for Multiobjective Test Problems With Difficult-to-Approximate Pareto Front Boundaries
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DOI：
10.1109/tevc.2018.2872453
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发表时间：
2019-08
影响因子：
14.3
通讯作者：
Zhenkun Wang;Y. Ong;Jianyong Sun;Abhishek Gupta;Qingfu Zhang
中科院分区：
文献类型：
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作者：
Zhenkun Wang;Y. Ong;Jianyong Sun;Abhishek Gupta;Qingfu Zhang
在一些实际应用中，人们发现当Pareto前沿（PF）的边界解比其他边界解更难近似时，多目标优化进化算法（moea）的性能可能会下降。在现有的多目标优化测试问题中，很少考虑这种问题特征，即难以近似（DtA） PF边界。为了填补这一空白并促进可能的系统研究，我们引入了一个新的测试问题生成器。所提出的发生器使设计具有可控困难的DtA - PF边界特征的测试问题成为可能。三种具有代表性的MOEA， NSGA-II， SMS-EMOA和MOEA/D-DRA，对使用所提出的发生器产生的一系列测试问题进行了执行。实验结果表明，这三种算法在新的测试问题上的表现都很差。同时，本文还验证了MOEA/D-DRA的改进变体MOEA/D-DRA- ut能够更有效地处理这些问题。结果表明，合理分配计算资源是moea处理DtA - PF边界问题的关键。
In some real-world applications, it has been found that the performance of multiobjective optimization evolutionary algorithms (MOEAs) may deteriorate when boundary solutions in the Pareto front (PF) are more difficult to approximate than others. Such a problem feature, referred to as difficult-to-approximate (DtA) PF boundaries, is seldom considered in existing multiobjective optimization test problems. To fill this gap and facilitate possible systematic studies, we introduce a new test problem generator. The proposed generator enables the design of test problems with controllable difficulties regarding the feature of DtA PF boundaries. Three representative MOEAs, NSGA-II, SMS-EMOA, and MOEA/D-DRA, are performed on a series of test problems created using the proposed generator. Experimental results indicate that all the three algorithms perform poorly on the new test problems. Meanwhile, a modified variant of MOEA/D-DRA, denoted as MOEA/D-DRA-UT, is validated to be more effective in dealing with these problems. Subsequently, it is concluded that the rational allocation of computational resources between different PF parts is crucial for MOEAs to handle the problems with DtA PF boundaries.